diff --git a/Dockerfile b/Dockerfile
index 148b87c4782675b92a9ebf99e774bb447a95c9ea..2e3fac845305b098091e97375bd2a3fcee06dc90 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -6,21 +6,26 @@ RUN apt-get update && apt-get install -y \
     libpng-dev libtiff5-dev libjpeg-dev \
     && rm -rf /var/lib/apt/lists/*
 
-
-RUN R -e "install.packages(c('shiny', 'shinydashboard', 'remotes'), repos='https://cran.rstudio.com/')"
+RUN R -e "install.packages(c('shiny', 'shinydashboard', 'remotes','readxl'), repos='https://cran.rstudio.com/',dependencies=TRUE)"
+RUN echo 'options(radiant.shinyFiles = FALSE)' >> /usr/local/lib/R/etc/Rprofile.site
 COPY . /srv/shiny-server/
 COPY set_path.R /usr/local/lib/R/etc/Rprofile.site.d/00-radiant-path.R
 
 # 安装所有子模块
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant.data', type='source', upgrade='never')"
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant.basics', type='source', upgrade='never')"
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant.model', type='source', upgrade='never')"
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant.multivariate', type='source', upgrade='never')"
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant.design', type='source', upgrade='never')"
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant.quickgen', type='source', upgrade='never')"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant.data',dependencies=TRUE, type='source', upgrade='never')"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant.basics',dependencies=TRUE, type='source', upgrade='never')"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant.model',dependencies=TRUE, type='source', upgrade='never')"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant.multivariate',dependencies=TRUE, type='source', upgrade='never')"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant.design',dependencies=TRUE, type='source', upgrade='never')"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant.quickgen',dependencies=TRUE, type='source', upgrade='never')"
 
 # 安装主 radiant 应用
-RUN R -e "remotes::install_local('/srv/shiny-server/radiant-master', type='source', upgrade='never')"
+RUN R -e "remotes::install_local('/srv/shiny-server/radiant-master',dependencies=TRUE, type='source', upgrade='never')"
 
 WORKDIR /data
-CMD ["R", "-e", "radiant::radiant(host='0.0.0.0', port=3838)"]
\ No newline at end of file
+CMD ["R", "-e", "radiant::radiant(host='0.0.0.0', port=3838)"]
+
+#docker images | grep radiant 查看镜像
+#sudo systemctl restart shinyproxy  重启proxy
+#sudo vim /etc/shinyproxy/application.yml 修改配置文件
+#docker build -t radiant:latest .   构建镜像
\ No newline at end of file
diff --git a/data/cancer.csv b/data/cancer.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4effa94c2e01d89df02881c117cf223919195c5b
--- /dev/null
+++ b/data/cancer.csv
@@ -0,0 +1,930 @@
+ID,Hospital,Treatment,Age,Sex,Blood test,Obstruct,Perfor,Adhere,Differ,Extent,Effect,Occurrence,OS_status,OS_time,Objective Response
+1,hospital_5,Lev,43,Male,3829,NA,No,No,Moderate,Serosa,Bad,5,1,1521,Yes
+2,hospital_3,Lev,63,Male,3825,No,No,No,Moderate,Serosa,Good,1,0,3087,No
+3,hospital_5,Obs,71,Female,3809,No,No,Yes,Moderate,Muscle,Bad,7,1,963,Yes
+4,hospital_4,Lev,66,Female,3808,Yes,No,No,Moderate,Serosa,Bad,6,1,293,Yes
+5,hospital_5,Obs,69,Male,3738,No,No,No,Moderate,Serosa,Bad,22,1,659,Yes
+6,hospital_4,Lev,57,Female,3714,No,No,No,Moderate,Serosa,Bad,9,1,1767,Yes
+7,hospital_2,Lev,77,Male,3692,No,No,No,Moderate,Serosa,Bad,5,1,420,Yes
+8,hospital_2,Obs,54,Male,3685,No,No,No,Moderate,Serosa,Good,1,0,3192,No
+9,hospital_2,Lev,46,Male,3673,No,No,Yes,Moderate,Serosa,Good,2,0,3173,Yes
+10,hospital_2,Lev,68,Female,3587,No,No,No,Moderate,Serosa,Bad,1,0,3308,Yes
+11,hospital_1,Lev,47,Female,3585,No,No,Yes,Moderate,Serosa,Bad,1,0,2908,No
+12,hospital_1,Lev,52,Male,3578,No,No,No,Poor,Serosa,Bad,2,0,3309,Yes
+13,hospital_3,Obs,64,Male,3530,No,No,No,Moderate,Serosa,Good,1,1,2085,Yes
+14,hospital_4,Lev,68,Male,3524,Yes,No,No,Moderate,Serosa,Good,3,1,2910,Yes
+15,hospital_1,Obs,46,Male,3519,Yes,No,No,Moderate,Serosa,Good,4,0,2754,Yes
+16,hospital_1,Obs,68,Male,3517,No,No,No,Moderate,Serosa,Good,1,0,3214,Yes
+17,hospital_4,Lev,62,Male,3500,Yes,No,Yes,Moderate,Serosa,Bad,6,1,406,Yes
+18,hospital_5,Lev,79,Male,3485,Yes,No,No,Moderate,Serosa,Bad,1,1,522,Yes
+19,hospital_1,Lev,34,Female,3469,Yes,No,No,Moderate,Muscle,Bad,1,1,887,No
+20,hospital_1,Lev,50,Female,3469,No,No,Yes,Moderate,Serosa,Good,1,0,3329,No
+21,hospital_2,Obs,64,Male,3458,NA,No,No,Moderate,Serosa,Good,1,1,2789,Yes
+22,hospital_4,Lev,56,Male,3451,Yes,No,No,Moderate,Serosa,Bad,4,1,739,Yes
+23,hospital_3,Lev,61,Female,3450,No,No,No,Moderate,Serosa,Bad,4,1,709,No
+24,hospital_1,Lev,50,Female,3441,No,No,No,Moderate,Muscle,Good,1,0,2969,Yes
+25,hospital_1,Lev,70,Female,3427,No,No,No,Moderate,Serosa,Good,4,0,2889,Yes
+26,hospital_5,Obs,73,Male,3425,No,No,No,Moderate,Serosa,Bad,1,1,1772,No
+27,hospital_5,Obs,70,Female,3418,No,No,Yes,Moderate,Serosa,Bad,13,1,384,Yes
+28,hospital_5,Lev,68,Female,3416,No,No,No,Moderate,Serosa,Bad,1,1,968,Yes
+29,hospital_4,Obs,56,Female,3415,Yes,No,No,Poor,Serosa,Bad,6,1,218,Yes
+30,hospital_5,Lev,80,Male,3413,No,No,No,Poor,Serosa,Bad,1,1,133,No
+31,hospital_2,Lev,64,Female,3410,No,No,No,Moderate,Submucosa,Good,1,0,3238,Yes
+32,hospital_3,Lev,33,Female,3408,Yes,No,No,Moderate,Serosa,Good,3,0,3019,Yes
+33,hospital_2,Obs,49,Female,3405,No,No,No,Moderate,Serosa,Bad,2,1,1745,No
+34,hospital_5,Obs,47,Male,3401,No,No,No,Moderate,Serosa,Good,3,1,2527,Yes
+35,hospital_4,Lev,56,Female,3399,No,No,No,Moderate,Serosa,Bad,1,1,1387,Yes
+36,hospital_4,Lev,72,Female,3399,No,No,Yes,Poor,Serosa,Good,1,0,3024,Yes
+37,hospital_5,Obs,79,Male,3389,No,No,No,Moderate,Serosa,Bad,19,1,570,Yes
+38,hospital_2,Obs,64,Female,3383,No,No,No,Poor,Serosa,Good,1,0,2815,Yes
+39,hospital_1,Lev,61,Male,3371,No,No,No,Poor,Serosa,Good,2,0,2901,Yes
+40,hospital_2,Lev,58,Male,3369,No,No,No,Moderate,Serosa,Bad,7,1,553,No
+41,hospital_3,Lev,75,Male,3362,No,No,No,Moderate,Serosa,Bad,2,1,905,Yes
+42,hospital_3,Obs,39,Female,3349,Yes,No,No,Well,Serosa,Good,1,0,3030,Yes
+43,hospital_3,Obs,71,Male,3342,Yes,No,No,Moderate,Muscle,Bad,3,1,685,Yes
+44,hospital_2,Lev,58,Female,3340,Yes,No,No,Moderate,Serosa,Good,2,0,2740,Yes
+45,hospital_3,Lev,40,Male,3335,No,No,No,Well,Serosa,Good,1,0,2899,No
+46,hospital_1,Obs,63,Female,3328,No,Yes,No,Moderate,Serosa,Good,2,0,2598,No
+47,hospital_1,Lev,59,Female,3326,No,No,No,Poor,Submucosa,Good,1,0,2840,Yes
+48,hospital_1,Lev,59,Female,3321,Yes,No,No,Well,Serosa,Good,2,0,2802,Yes
+49,hospital_4,Lev,59,Male,3320,No,No,No,Moderate,Serosa,Good,6,0,2781,Yes
+50,hospital_3,Lev,60,Male,3315,No,No,No,Poor,Serosa,Bad,5,1,833,Yes
+51,hospital_4,Obs,68,Female,3315,No,No,No,Moderate,Serosa,Bad,2,1,1290,No
+52,hospital_3,Lev,70,Female,3302,No,No,No,Moderate,Serosa,Bad,3,1,1620,Yes
+53,hospital_1,Obs,76,Male,3300,No,No,No,Moderate,Serosa,Good,2,0,2765,Yes
+54,hospital_4,Lev,45,Female,3294,No,No,No,Moderate,Serosa,Bad,3,0,2708,Yes
+55,hospital_3,Lev,61,Male,3289,No,No,No,Moderate,Muscle,Bad,2,0,2737,Yes
+56,hospital_4,Obs,76,Male,3289,No,No,No,Well,Serosa,Bad,3,1,1178,No
+57,hospital_3,Lev,53,Male,3281,No,No,No,Moderate,Serosa,Good,2,0,2765,Yes
+58,hospital_1,Lev,63,Female,3279,No,No,No,Moderate,Serosa,Good,5,0,2883,Yes
+59,hospital_2,Obs,65,Female,3275,No,No,No,Poor,Serosa,Good,6,0,2679,Yes
+60,hospital_3,Obs,57,Female,3272,Yes,No,No,Poor,Serosa,Good,4,0,2925,No
+61,hospital_4,Lev,80,Male,3265,No,Yes,No,Moderate,Serosa,Bad,4,1,472,Yes
+62,hospital_1,Lev,58,Male,3265,No,No,No,Well,Muscle,Good,1,0,2772,Yes
+63,hospital_5,Obs,53,Female,3265,No,No,No,Poor,Serosa,Bad,15,1,474,No
+64,hospital_3,Lev,53,Female,3264,Yes,No,No,NA,Serosa,Good,1,0,2739,Yes
+65,hospital_4,Obs,71,Female,3261,No,No,No,Well,Serosa,Bad,1,1,365,Yes
+66,hospital_1,Lev,66,Female,3261,No,No,No,Moderate,Serosa,Good,2,0,2653,Yes
+67,hospital_4,Lev,49,Male,3260,No,No,No,Poor,Serosa,Good,6,0,2726,No
+68,hospital_5,Obs,60,Male,3254,No,No,No,Moderate,Serosa,Bad,10,1,774,Yes
+69,hospital_3,Obs,70,Female,3254,No,No,No,Moderate,Submucosa,Good,3,0,3078,Yes
+70,hospital_4,Obs,40,Female,3247,No,No,No,Moderate,Serosa,Good,2,1,2133,No
+71,hospital_2,Lev,55,Female,3247,No,No,No,Moderate,Serosa,Good,1,1,2127,No
+72,hospital_4,Lev,56,Female,3243,No,No,No,Moderate,Serosa,Bad,15,1,400,Yes
+73,hospital_5,Lev,54,Male,3240,No,No,No,Moderate,Serosa,Good,9,0,3185,Yes
+74,hospital_5,Obs,49,Female,3239,Yes,No,No,Poor,Serosa,Bad,5,1,1237,Yes
+75,hospital_5,Lev,71,Female,3237,No,No,No,Moderate,Serosa,Bad,7,1,1219,No
+76,hospital_4,Obs,67,Female,3232,No,No,No,Moderate,Serosa,Good,4,0,3017,Yes
+77,hospital_2,Lev,68,Female,3231,No,No,No,Moderate,Serosa,Bad,5,1,806,Yes
+78,hospital_1,Lev,63,Male,3230,No,No,No,Moderate,Serosa,Good,2,0,2985,Yes
+79,hospital_2,Lev,50,Male,3230,Yes,No,Yes,Moderate,Serosa,Good,1,0,2969,Yes
+80,hospital_5,Lev,45,Female,3226,No,No,No,Moderate,Muscle,Good,7,1,1995,Yes
+81,hospital_3,Lev,66,Male,3226,No,No,No,Moderate,Muscle,Good,1,0,2958,Yes
+82,hospital_4,Obs,46,Female,3225,No,No,No,Poor,Serosa,Bad,1,1,1133,No
+83,hospital_5,Lev,70,Male,3224,No,No,No,NA,Muscle,Bad,3,1,1548,Yes
+84,hospital_1,Lev,63,Male,3223,Yes,No,No,Moderate,Muscle,Good,2,0,3085,Yes
+85,hospital_4,Lev,45,Male,3223,No,No,No,Poor,Serosa,Bad,8,1,736,No
+86,hospital_1,Lev,49,Female,3220,No,No,No,Moderate,Serosa,Good,1,0,2789,Yes
+87,hospital_2,Lev,62,Female,3218,No,No,No,Moderate,Muscle,Good,2,0,3325,Yes
+88,hospital_4,Obs,59,Male,3216,No,No,No,Moderate,Serosa,Bad,4,1,381,No
+89,hospital_1,Lev,80,Female,3213,NA,No,No,Well,Serosa,Good,4,0,2724,Yes
+90,hospital_3,Lev,73,Male,3211,Yes,No,No,NA,Serosa,Bad,4,1,997,Yes
+91,hospital_5,Obs,46,Male,3209,No,No,No,Moderate,Serosa,Bad,11,1,413,Yes
+92,hospital_2,Lev,64,Male,3208,No,No,No,Moderate,Serosa,Bad,4,1,708,Yes
+93,hospital_3,Lev,45,Male,3206,No,No,No,Moderate,Serosa,Good,9,0,2765,No
+94,hospital_3,Lev,26,Female,3203,No,No,Yes,Moderate,Adjacent structures,Bad,NA,0,2869,No
+95,hospital_1,Lev,66,Male,3199,NA,No,No,Moderate,Serosa,Bad,1,0,2918,Yes
+96,hospital_3,Lev,67,Male,3197,No,No,Yes,Moderate,Adjacent structures,Bad,2,1,2458,Yes
+97,hospital_5,Obs,65,Female,3195,No,No,No,Moderate,Adjacent structures,Bad,20,1,459,Yes
+98,hospital_2,Lev,74,Male,3191,No,No,Yes,Moderate,Serosa,Good,1,1,2318,Yes
+99,hospital_2,Lev,71,Male,3190,No,No,Yes,Moderate,Adjacent structures,Bad,NA,1,569,Yes
+100,hospital_5,Obs,58,Female,3188,No,No,Yes,Moderate,Muscle,Good,8,1,2077,Yes
+101,hospital_5,Obs,59,Male,3183,No,No,No,Moderate,Serosa,Bad,6,1,1216,Yes
+102,hospital_5,Lev,61,Male,3182,NA,No,No,Poor,Serosa,Bad,5,1,171,Yes
+103,hospital_4,Lev,49,Male,3179,No,No,No,Moderate,Serosa,Bad,2,1,712,Yes
+104,hospital_5,Lev,50,Female,3179,No,No,No,Moderate,Serosa,Bad,6,1,614,No
+105,hospital_1,Obs,75,Female,3178,No,No,No,Moderate,Serosa,Good,1,0,2849,No
+106,hospital_3,Obs,68,Male,3176,No,No,No,Poor,Serosa,Bad,3,1,1530,Yes
+107,hospital_4,Lev,60,Female,3174,No,No,Yes,Moderate,Serosa,Bad,10,1,402,Yes
+108,hospital_5,Lev,65,Female,3172,No,No,Yes,Moderate,Serosa,Bad,2,1,1511,Yes
+109,hospital_4,Lev,74,Female,3168,No,No,No,Moderate,Serosa,Good,5,0,2828,No
+110,hospital_2,Lev,52,Female,3163,No,No,No,Poor,Serosa,Bad,3,1,23,Yes
+111,hospital_1,Lev,64,Male,3156,No,No,Yes,Moderate,Serosa,Good,6,0,2941,Yes
+112,hospital_3,Lev,47,Male,3156,No,No,Yes,Moderate,Serosa,Bad,1,1,755,Yes
+113,hospital_1,Obs,45,Female,3153,No,No,No,Moderate,Submucosa,Good,1,0,2815,Yes
+114,hospital_5,Obs,61,Male,3151,Yes,No,Yes,Poor,Serosa,Bad,5,1,761,Yes
+115,hospital_2,Lev,53,Male,3148,No,No,No,Poor,Serosa,Good,2,1,1839,No
+116,hospital_4,Obs,60,Male,3131,Yes,No,No,Moderate,Serosa,Good,5,1,2351,Yes
+117,hospital_1,Lev,60,Female,3130,No,No,No,Moderate,Serosa,Good,1,0,2760,Yes
+118,hospital_1,Lev,51,Female,3128,No,No,No,Moderate,Serosa,Good,5,0,2951,No
+119,hospital_1,Lev,60,Female,3128,No,No,Yes,Moderate,Serosa,Good,1,0,2820,No
+120,hospital_5,Obs,64,Female,3121,No,No,No,Moderate,Serosa,Bad,1,1,1327,Yes
+121,hospital_2,Lev,52,Female,3118,No,No,No,Moderate,Serosa,Good,1,0,2678,Yes
+122,hospital_3,Lev,65,Female,3118,No,No,No,Poor,Serosa,Bad,2,1,226,No
+123,hospital_3,Lev,70,Female,3113,No,No,No,Moderate,Serosa,Good,1,0,2913,Yes
+124,hospital_2,Obs,55,Male,3100,No,No,No,Moderate,Serosa,Good,2,0,2862,Yes
+125,hospital_5,Lev,71,Male,3098,No,No,No,Poor,Serosa,Bad,5,1,454,Yes
+126,hospital_3,Obs,30,Male,3093,No,No,No,Moderate,Muscle,Good,1,0,2743,Yes
+127,hospital_2,Obs,40,Female,3092,No,No,No,Moderate,Serosa,Bad,3,1,1679,No
+128,hospital_5,Obs,31,Male,3092,Yes,No,No,Poor,Serosa,Bad,11,1,924,No
+129,hospital_3,Obs,53,Male,3090,No,No,No,Moderate,Muscle,Bad,1,1,721,No
+130,hospital_4,Obs,67,Male,3088,No,No,No,Moderate,Serosa,Bad,1,1,709,No
+131,hospital_3,Lev,58,Female,3080,No,No,No,Moderate,Serosa,Bad,1,1,961,No
+132,hospital_4,Lev,79,Female,3077,Yes,No,No,Poor,Serosa,Bad,2,1,326,Yes
+133,hospital_4,Lev,55,Female,3077,No,No,No,Poor,Muscle,Good,1,0,2703,Yes
+134,hospital_3,Obs,63,Female,3074,No,No,Yes,Moderate,Serosa,Bad,2,1,289,Yes
+135,hospital_3,Lev,55,Male,3072,Yes,No,No,Moderate,Serosa,Good,2,0,2905,No
+136,hospital_5,Lev,42,Male,3068,Yes,No,No,Moderate,Serosa,Bad,5,1,206,No
+137,hospital_2,Obs,56,Male,3065,No,No,No,Moderate,Serosa,Good,1,0,2618,Yes
+138,hospital_3,Lev,64,Female,3062,No,No,No,Moderate,Serosa,Bad,8,1,283,No
+139,hospital_2,Lev,55,Male,3058,Yes,No,No,Moderate,Serosa,Good,2,1,2718,Yes
+140,hospital_1,Obs,25,Female,3058,Yes,No,No,Moderate,Serosa,Good,7,0,2826,Yes
+141,hospital_4,Lev,59,Male,3055,No,No,No,Moderate,Serosa,Good,1,0,2916,Yes
+142,hospital_5,Lev,28,Male,3052,No,No,No,Poor,Serosa,Bad,9,1,499,No
+143,hospital_2,Lev,49,Female,3051,No,No,No,Well,Serosa,Good,NA,0,2950,Yes
+144,hospital_4,Obs,52,Female,3048,No,No,No,Moderate,Submucosa,Good,1,0,2899,Yes
+145,hospital_2,Obs,64,Female,3047,No,No,No,Poor,Serosa,Bad,5,1,673,Yes
+146,hospital_1,Obs,33,Female,3045,Yes,No,Yes,Well,Serosa,Good,1,0,3000,No
+147,hospital_4,Obs,76,Male,3044,No,No,No,Moderate,Serosa,Good,1,1,2284,No
+148,hospital_5,Lev,38,Male,3042,No,No,No,Well,Serosa,Bad,2,1,362,Yes
+149,hospital_2,Lev,53,Female,3041,Yes,Yes,No,Moderate,Serosa,Good,1,1,2152,Yes
+150,hospital_1,Obs,72,Female,3040,Yes,No,No,Moderate,Serosa,Good,2,0,2562,Yes
+151,hospital_1,Lev,46,Male,3038,No,No,No,Moderate,Serosa,Good,1,0,2730,Yes
+152,hospital_5,Lev,69,Female,3032,No,No,No,Moderate,Serosa,Bad,13,1,802,Yes
+153,hospital_5,Obs,43,Male,3030,Yes,No,No,Poor,Serosa,Bad,0,1,1166,Yes
+154,hospital_4,Lev,72,Male,3030,Yes,No,Yes,Moderate,Serosa,Bad,2,1,1193,No
+155,hospital_4,Lev,73,Male,3028,Yes,No,No,Moderate,Serosa,Bad,2,1,45,Yes
+156,hospital_1,Obs,68,Male,3027,No,No,No,Moderate,Serosa,Good,3,0,2577,Yes
+157,hospital_5,Obs,52,Female,3027,No,Yes,No,Well,Serosa,Bad,6,1,1136,No
+158,hospital_2,Lev,73,Female,3027,Yes,No,No,Moderate,Serosa,Good,2,0,2497,Yes
+159,hospital_3,Lev,66,Male,3025,Yes,No,No,Moderate,Serosa,Good,1,0,2648,Yes
+160,hospital_1,Obs,75,Female,3020,No,No,No,Poor,Serosa,Good,2,0,2458,No
+161,hospital_5,Lev,43,Male,3020,Yes,No,No,NA,Serosa,Bad,6,1,1135,Yes
+162,hospital_5,Lev,57,Female,3017,No,No,No,Moderate,Serosa,Bad,1,1,580,Yes
+163,hospital_4,Obs,74,Male,3017,Yes,No,No,Moderate,Serosa,Bad,6,1,485,Yes
+164,hospital_1,Lev,67,Female,3017,No,No,No,Moderate,Serosa,Good,1,0,2656,Yes
+165,hospital_4,Lev,66,Female,3013,No,No,Yes,Moderate,Serosa,Bad,2,1,806,Yes
+166,hospital_4,Obs,57,Male,3013,Yes,No,No,Moderate,Serosa,Good,3,0,2435,Yes
+167,hospital_2,Lev,81,Female,3009,No,No,No,Moderate,Serosa,Bad,3,1,1439,Yes
+168,hospital_3,Obs,50,Male,3007,No,No,No,Poor,Serosa,Bad,4,1,717,Yes
+169,hospital_4,Lev,62,Male,3006,Yes,Yes,No,Moderate,Serosa,Good,2,0,2568,Yes
+170,hospital_1,Lev,48,Female,3006,No,No,No,Well,Serosa,Good,4,0,2631,Yes
+171,hospital_3,Lev,45,Male,3005,No,No,No,Moderate,Muscle,NA,2,0,1474,No
+172,hospital_4,Lev,46,Male,3003,No,No,Yes,Moderate,Serosa,Good,2,1,2593,Yes
+173,hospital_3,Lev,72,Female,3001,No,No,No,Moderate,Serosa,Bad,2,1,1550,Yes
+174,hospital_2,Obs,55,Female,2997,No,No,No,Moderate,Serosa,Bad,4,1,670,Yes
+175,hospital_4,Lev,67,Male,2997,Yes,No,No,Moderate,Serosa,Bad,1,1,430,Yes
+176,hospital_3,Lev,41,Female,2996,No,No,No,Moderate,Serosa,Good,2,0,2821,Yes
+177,hospital_4,Lev,56,Male,2995,No,No,No,Moderate,Submucosa,Good,2,0,2672,Yes
+178,hospital_2,Lev,50,Male,2990,No,No,No,Moderate,Submucosa,Good,4,0,2699,No
+179,hospital_1,Lev,65,Female,2988,No,No,No,Well,Muscle,Good,1,0,2927,Yes
+180,hospital_2,Lev,74,Male,2988,No,No,Yes,Moderate,Serosa,Bad,1,1,993,No
+181,hospital_4,Obs,74,Female,2987,No,No,No,Moderate,Serosa,Good,2,0,2580,No
+182,hospital_4,Obs,58,Female,2987,No,No,No,Moderate,Serosa,Good,4,0,2621,Yes
+183,hospital_1,Lev,56,Female,2986,No,No,No,Poor,Serosa,Good,4,0,2779,Yes
+184,hospital_2,Obs,75,Female,2985,No,No,No,Moderate,Muscle,Good,1,0,2794,No
+185,hospital_1,Lev,67,Male,2984,No,No,No,Moderate,Serosa,Good,4,0,2656,Yes
+186,hospital_2,Lev,58,Female,2982,No,No,No,Well,Serosa,Good,6,0,2513,No
+187,hospital_1,Lev,58,Female,2981,No,No,No,Moderate,Serosa,Good,2,0,2488,No
+188,hospital_5,Lev,41,Male,2974,No,No,No,Poor,Serosa,Bad,33,1,1112,Yes
+189,hospital_1,Lev,72,Male,2972,No,No,No,Moderate,Serosa,Good,NA,0,2618,No
+190,hospital_4,Lev,48,Male,2972,No,No,Yes,NA,Serosa,Bad,2,1,795,Yes
+191,hospital_5,Lev,69,Female,2972,No,No,No,Moderate,Serosa,Bad,1,1,363,Yes
+192,hospital_5,Obs,57,Male,2967,Yes,No,Yes,Moderate,Serosa,Bad,1,1,949,No
+193,hospital_1,Lev,45,Female,2961,Yes,No,Yes,Moderate,Serosa,Bad,1,1,127,Yes
+194,hospital_2,Lev,76,Female,2960,No,No,No,Moderate,Serosa,Good,4,0,2871,No
+195,hospital_3,Obs,59,Male,2958,No,No,Yes,Moderate,Serosa,Good,2,0,2558,No
+196,hospital_2,Obs,66,Female,2958,No,No,No,Moderate,Serosa,Good,1,1,2083,No
+197,hospital_2,Obs,65,Female,2956,No,No,No,Poor,Muscle,Good,1,0,2747,Yes
+198,hospital_4,Lev,69,Male,2950,No,No,No,Well,Serosa,Bad,1,1,1105,Yes
+199,hospital_4,Lev,32,Female,2949,No,No,No,Poor,Serosa,Bad,NA,1,490,No
+200,hospital_2,Obs,56,Female,2949,No,No,No,NA,Muscle,Good,1,0,2507,Yes
+201,hospital_2,Lev,71,Male,2947,No,No,No,Well,Serosa,Bad,1,1,961,Yes
+202,hospital_5,Lev,75,Male,2945,No,No,No,NA,Serosa,Good,8,1,1879,Yes
+203,hospital_1,Lev,58,Male,2944,No,No,No,Poor,Serosa,Good,7,0,2592,Yes
+204,hospital_4,Obs,40,Female,2942,No,No,No,Moderate,Serosa,Good,4,1,2552,Yes
+205,hospital_4,Lev,39,Female,2941,No,No,No,Well,Submucosa,Good,2,0,2474,No
+206,hospital_1,Lev,42,Female,2939,No,No,No,Moderate,Serosa,Good,4,0,2349,No
+207,hospital_3,Lev,53,Female,2935,No,No,No,Well,Submucosa,Good,4,0,2835,Yes
+208,hospital_2,Obs,43,Male,2929,No,No,No,Moderate,Serosa,Good,2,0,2761,Yes
+209,hospital_3,Obs,51,Female,2923,No,No,No,Moderate,Serosa,Bad,4,1,411,Yes
+210,hospital_1,Lev,77,Male,2923,No,No,No,Well,Serosa,Good,2,0,2720,Yes
+211,hospital_2,Lev,67,Male,2922,Yes,No,No,Moderate,Serosa,Good,1,0,2495,Yes
+212,hospital_3,Obs,41,Male,2916,No,No,No,Moderate,Serosa,Bad,7,1,462,No
+213,hospital_1,Lev,63,Male,2914,Yes,Yes,Yes,Poor,Adjacent structures,Good,2,0,2497,Yes
+214,hospital_1,Lev,63,Male,2913,No,No,Yes,Moderate,Muscle,Good,3,0,2343,Yes
+215,hospital_4,Lev,63,Female,2910,No,No,No,Moderate,Serosa,Good,6,0,2630,Yes
+216,hospital_4,Lev,58,Female,2908,Yes,No,No,Moderate,Serosa,Good,8,0,2461,Yes
+217,hospital_3,Lev,67,Female,2896,No,No,No,Moderate,Adjacent structures,Good,4,0,2747,No
+218,hospital_5,Lev,55,Male,2894,Yes,No,No,Moderate,Serosa,Good,7,1,2482,Yes
+219,hospital_2,Lev,63,Male,2893,Yes,No,No,Poor,Serosa,Bad,5,1,580,Yes
+220,hospital_4,Lev,77,Male,2893,No,No,Yes,Moderate,Serosa,Bad,1,1,1215,Yes
+221,hospital_2,Lev,43,Male,2891,Yes,Yes,Yes,Poor,Serosa,Good,4,0,2525,Yes
+222,hospital_1,Lev,78,Female,2891,No,No,No,Moderate,Muscle,Good,2,0,2842,Yes
+223,hospital_5,Obs,51,Female,2887,No,No,Yes,Moderate,Serosa,Bad,5,1,1272,Yes
+224,hospital_2,Obs,67,Male,2886,Yes,No,No,Moderate,Serosa,Bad,1,1,438,No
+225,hospital_2,Lev,66,Male,2886,No,No,No,Moderate,Serosa,Good,1,0,2423,Yes
+226,hospital_4,Obs,64,Female,2885,No,No,Yes,Moderate,Adjacent structures,Bad,1,1,599,Yes
+227,hospital_2,Obs,75,Female,2884,Yes,No,Yes,Moderate,Serosa,Good,1,0,2706,Yes
+228,hospital_5,Lev,53,Male,2881,No,No,No,Moderate,Serosa,Good,1,1,2683,Yes
+229,hospital_3,Lev,48,Male,2880,Yes,Yes,No,Moderate,Serosa,Good,2,0,2723,Yes
+230,hospital_3,Obs,59,Female,2878,No,No,Yes,Moderate,Adjacent structures,Bad,1,1,1230,No
+231,hospital_3,Obs,60,Female,2875,No,No,No,Moderate,Serosa,Good,1,0,2731,Yes
+232,hospital_2,Obs,42,Male,2865,No,No,No,Moderate,Serosa,Good,2,0,2313,Yes
+233,hospital_3,Lev,60,Male,2864,No,No,No,Moderate,Muscle,Good,1,0,2484,No
+234,hospital_1,Lev,58,Male,2862,NA,No,No,Well,Serosa,Good,1,0,2754,Yes
+235,hospital_3,Lev,59,Male,2860,NA,No,No,Moderate,Muscle,Good,2,1,2725,Yes
+236,hospital_5,Obs,70,Female,2856,No,No,No,Moderate,Serosa,Bad,2,1,1295,Yes
+237,hospital_1,Lev,75,Female,2855,No,No,No,Moderate,Serosa,Good,3,0,2506,Yes
+238,hospital_3,Lev,73,Female,2853,No,No,No,Moderate,Serosa,Good,3,0,2713,Yes
+239,hospital_4,Obs,76,Male,2852,No,No,No,Moderate,Serosa,Good,1,0,2695,Yes
+240,hospital_5,Lev,68,Female,2852,No,No,No,Moderate,Serosa,Bad,3,1,1276,Yes
+241,hospital_3,Lev,61,Male,2851,No,No,No,Moderate,Adjacent structures,Good,2,0,2600,No
+242,hospital_2,Lev,76,Male,2850,NA,No,No,Moderate,Muscle,Good,1,0,2352,No
+243,hospital_1,Lev,56,Female,2850,No,Yes,Yes,Moderate,Serosa,Good,3,0,2775,Yes
+244,hospital_2,Lev,55,Female,2849,Yes,No,No,NA,Serosa,Good,2,0,2442,Yes
+245,hospital_3,Obs,60,Female,2847,Yes,No,Yes,Poor,Serosa,Bad,4,1,437,No
+246,hospital_3,Lev,72,Male,2845,No,No,No,Moderate,Serosa,Bad,9,1,1709,Yes
+247,hospital_3,Lev,74,Female,2843,Yes,No,No,Moderate,Serosa,Bad,11,1,1607,Yes
+248,hospital_3,Lev,62,Female,2839,No,No,No,Moderate,Serosa,Bad,3,1,1637,No
+249,hospital_4,Lev,76,Female,2832,No,No,No,Well,Serosa,Bad,1,1,1117,Yes
+250,hospital_2,Lev,72,Male,2832,No,No,No,Moderate,Serosa,Good,2,0,2732,Yes
+251,hospital_4,Lev,57,Male,2831,No,No,No,Poor,Serosa,Bad,2,1,222,Yes
+252,hospital_3,Obs,39,Female,2831,No,No,No,Moderate,Adjacent structures,Good,1,0,2688,No
+253,hospital_3,Lev,61,Male,2831,No,No,No,Moderate,Serosa,Good,1,0,2520,Yes
+254,hospital_5,Obs,62,Female,2830,No,No,No,Poor,Serosa,Bad,5,1,595,Yes
+255,hospital_4,Lev,70,Male,2826,No,No,No,Moderate,Serosa,Bad,2,1,343,No
+256,hospital_4,Obs,70,Female,2825,No,No,No,Moderate,Serosa,Bad,5,1,874,Yes
+257,hospital_5,Lev,57,Female,2824,Yes,No,No,Moderate,Serosa,Bad,8,1,232,Yes
+258,hospital_3,Lev,65,Male,2823,No,No,No,Moderate,Muscle,Good,3,0,2558,Yes
+259,hospital_3,Lev,65,Female,2821,No,No,No,Moderate,Serosa,Good,1,0,2711,Yes
+260,hospital_5,Obs,71,Female,2818,No,No,No,Moderate,Serosa,Bad,15,1,113,Yes
+261,hospital_5,Lev,70,Female,2816,Yes,No,No,Moderate,Serosa,Bad,3,1,643,Yes
+262,hospital_2,Obs,36,Female,2813,No,No,No,Moderate,Serosa,Good,1,0,2413,No
+263,hospital_1,Lev,48,Male,2813,No,No,No,Moderate,Submucosa,Good,2,0,2509,Yes
+264,hospital_1,Lev,53,Male,2812,No,No,No,Well,Serosa,Good,1,0,2356,Yes
+265,hospital_5,Lev,54,Male,2810,No,No,No,Moderate,Serosa,Bad,3,1,1279,Yes
+266,hospital_3,Lev,58,Male,2809,No,No,No,Well,Serosa,Bad,3,1,938,Yes
+267,hospital_3,Obs,67,Male,2804,No,No,No,Moderate,Serosa,Good,3,0,2761,No
+268,hospital_3,Lev,59,Male,2803,Yes,No,No,Moderate,Serosa,Good,2,0,2386,No
+269,hospital_2,Obs,67,Female,2800,No,No,Yes,Moderate,Serosa,Bad,4,1,433,Yes
+270,hospital_2,Lev,60,Female,2799,Yes,No,No,Poor,Serosa,Good,1,0,2445,Yes
+271,hospital_1,Lev,70,Female,2799,No,No,No,Moderate,Muscle,Good,1,0,2280,Yes
+272,hospital_3,Obs,76,Male,3194,No,No,No,Well,Serosa,Bad,3,1,311,Yes
+273,hospital_4,Lev,60,Male,3192,Yes,No,No,Well,Serosa,Bad,1,1,977,No
+274,hospital_5,Obs,67,Female,3190,Yes,No,No,Well,Serosa,Bad,12,1,833,Yes
+275,hospital_4,Lev,53,Male,3189,No,No,No,Moderate,Serosa,Bad,3,1,582,Yes
+276,hospital_4,Lev,76,Female,3187,No,No,No,Well,Serosa,Good,1,0,2541,Yes
+277,hospital_4,Obs,74,Male,3184,No,No,No,Moderate,Serosa,Bad,2,1,238,Yes
+278,hospital_2,Obs,56,Female,3184,Yes,No,No,Moderate,Adjacent structures,Good,6,1,2257,No
+279,hospital_4,Lev,65,Female,3180,No,No,No,Moderate,Muscle,Good,1,0,2501,Yes
+280,hospital_2,Lev,63,Male,3179,No,No,No,Moderate,Serosa,Bad,2,1,1798,Yes
+281,hospital_2,Obs,56,Male,3178,No,No,No,Moderate,Serosa,Bad,2,1,883,Yes
+282,hospital_3,Lev,70,Female,3178,No,No,Yes,Poor,Serosa,Good,4,0,2548,No
+283,hospital_3,Lev,48,Female,3177,No,No,No,Moderate,Serosa,Good,9,0,2527,Yes
+284,hospital_2,Lev,45,Male,3174,Yes,No,No,Moderate,Serosa,Good,2,0,2263,Yes
+285,hospital_4,Lev,68,Female,3170,No,No,No,Moderate,Serosa,Bad,8,1,706,No
+286,hospital_1,Lev,57,Female,3169,No,No,No,Moderate,Muscle,Good,1,0,2588,Yes
+287,hospital_5,Lev,70,Male,3167,No,No,No,Moderate,Muscle,Good,1,1,2542,Yes
+288,hospital_1,Lev,39,Male,3165,No,No,No,Moderate,Serosa,NA,1,0,1279,Yes
+289,hospital_1,Obs,46,Male,3164,No,No,Yes,Poor,Adjacent structures,Bad,1,1,1304,No
+290,hospital_2,Obs,77,Female,3163,Yes,No,No,Moderate,Serosa,Good,4,0,2324,Yes
+291,hospital_1,Lev,59,Male,3163,NA,No,No,Well,Serosa,Good,1,0,2488,Yes
+292,hospital_4,Lev,58,Female,3161,No,No,No,Moderate,Serosa,Good,1,0,2628,No
+293,hospital_2,Obs,56,Male,3157,No,No,No,Moderate,Serosa,Good,8,0,2800,No
+294,hospital_1,Lev,68,Male,3157,No,No,No,NA,Serosa,Good,2,0,2456,Yes
+295,hospital_2,Obs,57,Female,3155,No,Yes,Yes,Moderate,Serosa,Good,1,0,2503,Yes
+296,hospital_4,Lev,44,Female,3154,No,No,No,Moderate,Serosa,Bad,3,1,1446,Yes
+297,hospital_5,Lev,56,Male,3152,No,No,Yes,Moderate,Serosa,Bad,3,1,641,No
+298,hospital_5,Obs,67,Male,3150,No,No,No,Moderate,Serosa,Bad,4,1,1788,Yes
+299,hospital_3,Lev,62,Male,3150,No,No,No,Moderate,Muscle,Good,6,0,2304,Yes
+300,hospital_3,Lev,68,Female,3145,No,No,No,Moderate,Serosa,Bad,7,1,944,Yes
+301,hospital_3,Lev,61,Male,3144,No,No,No,Moderate,Muscle,Good,2,0,2679,Yes
+302,hospital_3,Lev,44,Female,3142,Yes,No,No,Moderate,Serosa,Bad,5,1,559,Yes
+303,hospital_2,Lev,52,Female,3140,No,No,No,Moderate,Serosa,Good,7,0,2663,Yes
+304,hospital_3,Lev,51,Male,3137,Yes,No,No,Poor,Serosa,Bad,1,1,647,No
+305,hospital_1,Obs,59,Female,3135,No,No,No,Moderate,Serosa,Good,9,0,2697,Yes
+306,hospital_3,Lev,61,Male,3134,No,No,No,Poor,Serosa,Good,1,0,2538,Yes
+307,hospital_2,Obs,57,Female,3132,No,No,No,Poor,Serosa,Good,2,0,2219,No
+308,hospital_3,Lev,65,Male,3131,No,No,No,Moderate,Serosa,Good,1,0,2487,Yes
+309,hospital_4,Lev,73,Female,3131,Yes,No,No,Moderate,Serosa,Good,1,0,2709,Yes
+310,hospital_5,Obs,69,Female,3129,No,No,No,Poor,Serosa,Bad,6,1,840,No
+311,hospital_1,Lev,63,Male,3129,No,No,No,Moderate,Serosa,Good,1,0,2267,Yes
+312,hospital_3,Lev,75,Male,3127,No,No,No,Moderate,Muscle,Good,2,0,2444,Yes
+313,hospital_2,Lev,64,Female,3127,No,No,No,Well,Serosa,Good,5,0,2393,Yes
+314,hospital_1,Obs,56,Female,3122,No,No,No,Well,Submucosa,Good,1,0,2237,Yes
+315,hospital_2,Lev,69,Male,3121,No,No,No,Moderate,Serosa,Good,2,0,2915,No
+316,hospital_2,Lev,64,Female,3119,No,No,No,Moderate,Serosa,Good,2,0,2467,No
+317,hospital_2,Lev,74,Female,3119,Yes,No,No,Moderate,Serosa,Bad,2,1,1092,Yes
+318,hospital_3,Lev,72,Male,3113,No,No,No,Moderate,Muscle,Good,4,0,2726,Yes
+319,hospital_4,Lev,58,Male,3113,Yes,No,No,Moderate,Serosa,Good,9,0,2764,Yes
+320,hospital_3,Lev,74,Female,3112,No,No,Yes,Poor,Adjacent structures,Good,15,0,2592,Yes
+321,hospital_1,Obs,61,Female,3112,No,No,No,Well,Muscle,Good,2,0,2730,Yes
+322,hospital_1,Obs,74,Female,3110,NA,No,No,Moderate,Muscle,Good,1,1,2287,Yes
+323,hospital_3,Lev,64,Male,3110,No,No,No,Moderate,Serosa,Good,5,0,2117,Yes
+324,hospital_5,Lev,71,Female,3109,No,No,No,Moderate,Serosa,Bad,20,1,1668,Yes
+325,hospital_1,Obs,66,Female,3107,No,No,Yes,NA,Adjacent structures,Bad,1,1,528,Yes
+326,hospital_1,Obs,53,Female,3104,Yes,No,No,Well,Serosa,Good,2,0,2651,No
+327,hospital_1,Lev,76,Female,3104,Yes,No,No,Moderate,Serosa,Good,1,0,2676,No
+328,hospital_5,Lev,75,Female,3103,Yes,No,Yes,Moderate,Muscle,Good,3,1,1885,Yes
+329,hospital_4,Lev,64,Male,3102,No,No,No,NA,Serosa,Good,3,0,2350,Yes
+330,hospital_5,Lev,65,Male,3100,No,No,No,Moderate,Serosa,Bad,8,1,475,Yes
+331,hospital_3,Obs,57,Female,3100,No,No,No,Moderate,Serosa,Bad,5,1,1246,No
+332,hospital_3,Lev,65,Male,3098,No,No,Yes,Poor,Serosa,Good,1,0,2204,Yes
+333,hospital_1,Obs,53,Male,3098,No,No,No,Moderate,Adjacent structures,Good,2,0,2716,Yes
+334,hospital_2,Lev,74,Male,3097,No,No,No,Moderate,Serosa,Bad,4,1,797,Yes
+335,hospital_2,Lev,74,Male,3095,No,No,No,Moderate,Serosa,Good,1,0,2527,Yes
+336,hospital_4,Lev,74,Female,3094,No,No,Yes,Poor,Serosa,Good,1,1,2021,Yes
+337,hospital_3,Lev,48,Female,3092,No,No,No,Moderate,Serosa,Bad,6,1,498,No
+338,hospital_3,Lev,58,Male,3091,No,No,No,Poor,Serosa,Bad,NA,1,885,Yes
+339,hospital_4,Lev,74,Female,3091,No,No,No,Moderate,Serosa,Bad,3,1,802,Yes
+340,hospital_1,Lev,71,Female,3091,No,No,No,Moderate,Serosa,Good,1,0,2674,No
+341,hospital_2,Obs,54,Female,3091,No,No,No,Moderate,Serosa,Bad,2,1,743,No
+342,hospital_4,Lev,80,Male,3090,No,No,No,Moderate,Muscle,Good,4,0,2517,Yes
+343,hospital_5,Lev,70,Male,3090,No,No,Yes,Moderate,Serosa,Bad,8,1,349,Yes
+344,hospital_3,Lev,70,Male,3089,Yes,No,No,Moderate,Serosa,Good,1,0,2723,No
+345,hospital_2,Obs,70,Male,3089,NA,No,No,Poor,Serosa,Bad,1,1,775,Yes
+346,hospital_2,Obs,71,Male,3088,No,No,No,Moderate,Serosa,Good,4,0,2326,Yes
+347,hospital_4,Obs,59,Male,3087,No,No,No,Moderate,Serosa,Bad,2,1,1134,Yes
+348,hospital_3,Lev,47,Male,3087,No,No,No,NA,Serosa,Bad,2,1,602,Yes
+349,hospital_1,Lev,63,Male,3086,No,No,No,Poor,Serosa,Good,2,0,2547,No
+350,hospital_3,Lev,69,Female,3085,No,No,No,Moderate,Serosa,Bad,7,1,940,No
+351,hospital_1,Lev,73,Female,3084,No,No,No,Moderate,Serosa,Good,1,0,2496,No
+352,hospital_1,Obs,67,Male,3083,No,No,No,Moderate,Serosa,Good,1,0,2628,No
+353,hospital_1,Lev,55,Female,3083,No,No,No,Moderate,Serosa,Good,1,0,2353,No
+354,hospital_2,Obs,45,Male,3081,No,No,No,Moderate,Serosa,Good,2,0,2184,Yes
+355,hospital_3,Lev,78,Female,3080,Yes,No,No,Moderate,Serosa,Good,3,0,2219,Yes
+356,hospital_2,Lev,80,Male,3079,No,No,No,Moderate,Serosa,Bad,3,1,191,Yes
+357,hospital_3,Obs,55,Male,3076,No,No,No,Moderate,Serosa,Bad,8,1,421,No
+358,hospital_2,Lev,64,Female,3076,Yes,No,No,Moderate,Serosa,Good,NA,0,2362,No
+359,hospital_5,Lev,60,Female,3074,No,Yes,No,Moderate,Serosa,Bad,10,1,952,Yes
+360,hospital_5,Lev,74,Female,3074,No,No,No,Moderate,Serosa,Bad,5,1,911,No
+361,hospital_5,Lev,61,Female,3073,No,No,No,Moderate,Serosa,Good,1,1,1851,Yes
+362,hospital_1,Obs,64,Male,3071,No,No,No,Moderate,Muscle,Good,4,0,2423,Yes
+363,hospital_4,Obs,48,Female,3071,No,No,Yes,Poor,Serosa,Bad,1,1,464,Yes
+364,hospital_5,Lev,76,Male,3070,No,No,No,Moderate,Serosa,Bad,2,1,443,No
+365,hospital_3,Lev,76,Female,3070,No,No,No,Poor,Serosa,Bad,NA,1,186,Yes
+366,hospital_1,Lev,50,Female,3070,No,No,No,Moderate,Serosa,Good,4,0,2545,Yes
+367,hospital_5,Lev,56,Male,3069,No,No,No,Moderate,Adjacent structures,Bad,3,1,356,Yes
+368,hospital_4,Lev,42,Female,3067,No,No,No,Poor,Serosa,Bad,10,1,484,No
+369,hospital_2,Lev,72,Female,3067,No,No,No,Moderate,Serosa,Bad,1,1,382,No
+370,hospital_5,Obs,68,Female,3065,No,No,Yes,Moderate,Serosa,Bad,9,1,1021,Yes
+371,hospital_2,Lev,49,Male,3064,No,No,No,Moderate,Muscle,Good,1,0,2472,Yes
+372,hospital_5,Lev,64,Male,3064,No,No,No,Moderate,Serosa,Good,12,0,2352,Yes
+373,hospital_2,Obs,70,Female,3062,NA,No,No,Well,Muscle,Good,1,0,2486,Yes
+374,hospital_2,Lev,50,Male,3062,No,No,Yes,Moderate,Adjacent structures,Bad,2,1,324,Yes
+375,hospital_1,Obs,74,Male,3061,No,No,Yes,Poor,Serosa,Good,3,0,2517,Yes
+376,hospital_4,Lev,37,Female,3058,No,No,No,Moderate,Serosa,Good,1,0,2613,No
+377,hospital_2,Lev,75,Female,3057,NA,No,No,Poor,Serosa,Good,1,0,2450,Yes
+378,hospital_5,Obs,56,Female,3056,No,No,No,Poor,Serosa,Bad,2,1,770,Yes
+379,hospital_2,Lev,74,Male,3054,No,No,No,Well,Serosa,Good,3,0,2490,No
+380,hospital_5,Obs,63,Male,3053,No,No,No,Moderate,Serosa,Bad,2,1,1548,Yes
+381,hospital_3,Lev,56,Male,3052,No,No,No,Moderate,Muscle,Good,2,0,2449,Yes
+382,hospital_5,Lev,42,Male,3052,No,No,No,Moderate,Serosa,Good,13,0,2299,No
+383,hospital_2,Lev,63,Male,3049,No,No,No,Moderate,Serosa,Bad,NA,1,1252,Yes
+384,hospital_2,Lev,62,Female,3048,No,No,No,Moderate,Serosa,Bad,2,1,730,Yes
+385,hospital_1,Lev,33,Female,3047,No,No,No,Moderate,Serosa,Good,2,0,2460,Yes
+386,hospital_5,Obs,50,Female,3047,No,No,No,Moderate,Serosa,Bad,8,1,499,Yes
+387,hospital_5,Lev,73,Male,3044,No,No,No,Poor,Serosa,Bad,6,1,129,Yes
+388,hospital_5,Lev,61,Female,3042,No,No,No,Poor,Serosa,Bad,9,1,52,Yes
+389,hospital_3,Obs,70,Male,3039,Yes,Yes,No,Moderate,Serosa,Good,1,1,2171,Yes
+390,hospital_3,Lev,38,Female,3038,No,No,No,Moderate,Serosa,Bad,3,1,1178,Yes
+391,hospital_4,Obs,64,Female,3038,Yes,No,No,Moderate,Serosa,Good,3,1,1915,Yes
+392,hospital_1,Lev,39,Female,3038,No,No,No,Moderate,Serosa,Good,2,0,2572,Yes
+393,hospital_1,Lev,47,Female,3036,No,No,No,Moderate,Serosa,Good,1,0,2590,No
+394,hospital_4,Obs,76,Male,3033,No,No,Yes,Poor,Serosa,Bad,13,1,215,Yes
+395,hospital_2,Obs,65,Male,3032,No,No,No,Moderate,Serosa,Good,2,0,2325,Yes
+396,hospital_3,Lev,43,Female,3030,Yes,No,No,Moderate,Serosa,Bad,4,1,961,Yes
+397,hospital_3,Lev,72,Male,3030,No,No,No,Moderate,Serosa,Good,1,0,2691,Yes
+398,hospital_3,Obs,33,Male,3029,No,No,No,Moderate,Serosa,Good,2,0,2574,Yes
+399,hospital_4,Lev,66,Male,3028,No,No,No,Moderate,Serosa,Good,7,0,2540,Yes
+400,hospital_1,Lev,74,Female,3027,No,No,No,Moderate,Serosa,Good,2,0,2364,No
+401,hospital_1,Lev,54,Male,3026,No,No,No,Moderate,Serosa,Good,1,0,2472,Yes
+402,hospital_5,Obs,44,Male,3022,No,No,No,Moderate,Serosa,Bad,14,1,409,No
+403,hospital_5,Obs,75,Male,3022,Yes,No,No,Moderate,Muscle,Bad,27,1,961,No
+404,hospital_4,Lev,58,Male,3020,No,No,No,Moderate,Serosa,Good,6,0,2449,Yes
+405,hospital_1,Lev,48,Male,3020,No,No,No,Well,Muscle,Good,6,0,2520,Yes
+406,hospital_3,Lev,64,Female,3018,No,No,No,Moderate,Serosa,Bad,1,1,916,No
+407,hospital_2,Lev,49,Male,3017,NA,No,No,Well,Serosa,Good,1,0,2227,Yes
+408,hospital_2,Obs,55,Female,3014,No,No,No,Moderate,Serosa,Good,1,0,2394,No
+409,hospital_1,Lev,60,Male,3013,No,No,No,Moderate,Serosa,Bad,3,0,2029,No
+410,hospital_3,Obs,67,Male,3011,No,No,No,Moderate,Serosa,Bad,2,0,2487,Yes
+411,hospital_3,Lev,79,Male,3011,No,No,No,Moderate,Muscle,Bad,1,1,2052,No
+412,hospital_1,Lev,57,Male,3011,No,No,No,Moderate,Serosa,Good,1,0,2690,Yes
+413,hospital_2,Obs,22,Female,3010,No,No,No,Moderate,Serosa,Good,3,0,2234,Yes
+414,hospital_5,Obs,59,Male,3007,Yes,No,No,Well,Serosa,Bad,4,1,537,No
+415,hospital_2,Lev,66,Female,3003,Yes,No,No,Well,Serosa,Good,1,0,2277,Yes
+416,hospital_2,Lev,54,Male,3001,No,No,Yes,Moderate,Adjacent structures,Bad,2,1,729,No
+417,hospital_4,Obs,58,Male,3000,No,No,No,Moderate,Muscle,Good,1,0,2194,No
+418,hospital_1,Obs,36,Female,2999,Yes,No,No,Moderate,Serosa,Good,7,0,2551,No
+419,hospital_5,Obs,52,Male,2999,No,No,No,Moderate,Serosa,Bad,4,1,1692,Yes
+420,hospital_5,Obs,61,Female,2997,No,No,No,Moderate,Serosa,Bad,1,1,758,Yes
+421,hospital_4,Lev,76,Female,2993,No,No,No,Well,Serosa,Good,2,1,2079,No
+422,hospital_3,Lev,58,Female,2993,No,No,Yes,Well,Serosa,Bad,6,1,720,Yes
+423,hospital_3,Lev,52,Male,2985,No,No,No,Well,Serosa,Good,5,0,2380,Yes
+424,hospital_4,Obs,72,Male,2984,No,No,No,Moderate,Serosa,Bad,1,1,845,Yes
+425,hospital_4,Lev,74,Male,2983,No,No,No,Well,Serosa,Good,1,0,2416,Yes
+426,hospital_4,Obs,62,Male,2979,No,No,No,Moderate,Muscle,Bad,6,1,863,Yes
+427,hospital_2,Obs,46,Female,2977,No,No,Yes,Moderate,Serosa,Bad,1,1,1363,No
+428,hospital_2,Obs,66,Male,2976,No,No,No,Moderate,Serosa,Good,1,0,2528,No
+429,hospital_2,Lev,52,Male,2976,No,No,No,Moderate,Serosa,Bad,5,1,1145,Yes
+430,hospital_5,Lev,38,Female,2976,No,No,No,NA,Serosa,Bad,24,1,499,Yes
+431,hospital_4,Obs,61,Male,2976,No,No,No,Moderate,Serosa,Bad,1,1,242,Yes
+432,hospital_1,Obs,60,Female,2972,No,No,No,Well,Serosa,Good,1,0,2294,Yes
+433,hospital_2,Lev,68,Female,2970,No,No,Yes,Well,Serosa,Bad,2,1,858,Yes
+434,hospital_5,Lev,53,Female,2966,No,No,No,Moderate,Serosa,Bad,6,1,122,No
+435,hospital_3,Lev,58,Male,2966,No,No,No,Moderate,Serosa,Bad,1,0,2682,Yes
+436,hospital_3,Obs,64,Male,2966,No,No,No,Moderate,Serosa,Bad,4,1,1818,Yes
+437,hospital_1,Obs,68,Male,2965,Yes,No,Yes,Moderate,Serosa,Good,3,0,2532,Yes
+438,hospital_2,Obs,62,Male,2958,No,No,Yes,Moderate,Adjacent structures,Bad,6,1,331,Yes
+439,hospital_2,Obs,70,Male,2955,No,No,No,Well,Serosa,Bad,1,1,1048,No
+440,hospital_3,Lev,57,Male,2952,No,No,No,Moderate,Serosa,Good,1,0,2513,Yes
+441,hospital_1,Lev,66,Female,2950,No,No,Yes,Moderate,Adjacent structures,Bad,1,1,340,Yes
+442,hospital_3,Lev,59,Female,2947,NA,No,No,Moderate,Serosa,Good,11,1,1850,Yes
+443,hospital_1,Lev,75,Male,2943,No,No,No,Well,Serosa,Good,3,0,2332,Yes
+444,hospital_3,Lev,77,Male,2930,No,No,No,Moderate,Serosa,Good,2,0,2279,Yes
+445,hospital_5,Lev,57,Male,2929,No,No,No,Moderate,Serosa,Bad,6,1,1041,Yes
+446,hospital_3,Obs,72,Male,2925,No,No,No,Well,Muscle,Bad,2,1,1790,No
+447,hospital_3,Lev,64,Female,2923,Yes,No,No,Moderate,Serosa,Bad,3,1,304,Yes
+448,hospital_2,Lev,33,Male,2923,No,No,No,Poor,Serosa,Bad,2,0,2517,Yes
+449,hospital_3,Lev,62,Female,2921,No,No,No,Moderate,Serosa,Bad,2,0,2156,Yes
+450,hospital_4,Lev,70,Male,2920,No,No,No,Moderate,Serosa,Bad,1,1,1388,Yes
+451,hospital_2,Lev,55,Female,2918,Yes,No,No,Well,Serosa,Good,4,0,2544,Yes
+452,hospital_2,Obs,32,Male,2908,Yes,No,Yes,Moderate,Serosa,Good,11,0,1852,No
+453,hospital_2,Obs,64,Female,2908,Yes,No,No,Moderate,Muscle,Good,2,0,2122,Yes
+454,hospital_1,Obs,48,Female,2906,No,No,No,Moderate,Adjacent structures,Good,1,0,2577,Yes
+455,hospital_4,Lev,68,Male,2906,No,No,Yes,Moderate,Serosa,Good,3,1,2023,No
+456,hospital_2,Lev,59,Female,2901,No,No,No,Moderate,Serosa,Bad,1,1,1201,Yes
+457,hospital_4,Obs,68,Male,2897,No,No,Yes,Poor,Serosa,Bad,9,1,901,Yes
+458,hospital_3,Lev,50,Female,2895,No,No,Yes,Well,Serosa,Good,1,0,2385,Yes
+459,hospital_2,Obs,41,Female,2895,Yes,No,No,Moderate,Serosa,Bad,4,1,663,Yes
+460,hospital_2,Lev,69,Female,2892,No,No,Yes,Moderate,Serosa,Good,1,0,2506,Yes
+461,hospital_1,Lev,46,Male,2890,No,No,No,Well,Muscle,Good,2,0,2332,Yes
+462,hospital_4,Obs,43,Male,2885,No,No,No,Moderate,Serosa,Good,1,0,2176,Yes
+463,hospital_3,Lev,68,Male,2881,No,No,No,Poor,Serosa,Bad,3,1,1212,No
+464,hospital_4,Lev,73,Male,2880,No,No,No,Moderate,Serosa,Bad,3,1,890,No
+465,hospital_5,Lev,66,Female,2876,No,No,Yes,Poor,Adjacent structures,Bad,4,1,302,Yes
+466,hospital_1,Obs,60,Female,2876,No,No,Yes,Moderate,Serosa,Good,1,0,2396,Yes
+467,hospital_1,Lev,74,Male,2871,No,No,No,Moderate,Serosa,Good,2,0,2481,No
+468,hospital_5,Lev,68,Male,2869,No,No,No,Well,Serosa,Bad,1,1,316,Yes
+469,hospital_1,Lev,60,Female,2868,Yes,No,No,Moderate,Serosa,Good,1,0,2245,Yes
+470,hospital_2,Obs,71,Male,2864,No,No,Yes,Moderate,Adjacent structures,Good,1,0,2447,No
+471,hospital_3,Obs,76,Male,2850,No,No,No,Moderate,Submucosa,Good,2,0,2213,Yes
+472,hospital_5,Obs,57,Male,2844,No,No,No,Poor,Muscle,Bad,8,1,1070,Yes
+473,hospital_4,Lev,33,Female,3102.4,No,No,No,Poor,Serosa,Bad,7,1,439,Yes
+474,hospital_3,Lev,54,Male,3096,No,No,No,Moderate,Serosa,Bad,4,1,905,No
+475,hospital_5,Obs,68,Male,3091.2,No,No,No,Moderate,Serosa,Bad,13,1,1723,Yes
+476,hospital_5,Obs,70,Female,3086.4,No,No,No,Poor,Muscle,Bad,6,1,241,Yes
+477,hospital_5,Obs,66,Male,3086.4,No,No,No,Moderate,Serosa,Bad,5,1,1314,No
+478,hospital_5,Lev,45,Female,3068.8,Yes,No,No,Moderate,Serosa,Bad,3,1,438,Yes
+479,hospital_1,Lev,61,Female,3068.8,No,No,No,Moderate,Serosa,Good,2,0,1981,Yes
+480,hospital_1,Obs,74,Female,3064,No,No,Yes,Poor,Serosa,Good,1,0,2195,Yes
+481,hospital_4,Obs,47,Male,3060.8,Yes,Yes,Yes,Moderate,Serosa,Bad,4,1,1101,Yes
+482,hospital_5,Lev,58,Female,3051.2,Yes,No,No,Poor,Serosa,Bad,5,1,79,Yes
+483,hospital_5,Obs,73,Male,3048,No,No,No,Moderate,Serosa,Bad,1,1,976,Yes
+484,hospital_5,Lev,61,Male,3048,No,No,No,Moderate,Serosa,Bad,17,1,664,No
+485,hospital_4,Obs,44,Female,3043.2,No,No,No,Moderate,Serosa,Good,4,0,2299,Yes
+486,hospital_4,Lev,56,Male,3043.2,No,No,No,Moderate,Serosa,Bad,1,1,279,Yes
+487,hospital_5,Lev,66,Female,3033.6,No,No,No,Moderate,Serosa,Bad,7,1,1037,Yes
+488,hospital_5,Obs,30,Female,3025.6,No,No,No,Poor,Serosa,Bad,6,1,692,Yes
+489,hospital_5,Lev,67,Female,3016,No,No,Yes,Moderate,Serosa,Good,10,1,2174,No
+490,hospital_1,Lev,74,Female,3014.4,No,No,No,Moderate,Serosa,Good,2,0,2144,No
+491,hospital_4,Lev,74,Female,3006.4,No,No,Yes,Poor,Serosa,Good,1,0,2058,Yes
+492,hospital_4,Obs,56,Male,3006.4,No,No,No,Moderate,Serosa,Good,4,0,2485,Yes
+493,hospital_1,Lev,60,Female,3000,No,No,No,Moderate,Serosa,Good,2,0,2410,Yes
+494,hospital_1,Lev,54,Female,3000,Yes,No,Yes,Poor,Muscle,Good,2,0,2565,Yes
+495,hospital_5,Lev,74,Female,2992,No,No,No,Moderate,Muscle,Bad,3,1,884,No
+496,hospital_3,Lev,45,Female,2982.4,No,No,No,Moderate,Serosa,Bad,3,1,389,Yes
+497,hospital_5,Lev,81,Female,2977.6,No,No,No,Moderate,Serosa,Bad,1,1,692,Yes
+498,hospital_4,Lev,73,Male,2969.6,Yes,No,No,Moderate,Serosa,Bad,1,1,642,Yes
+499,hospital_3,Lev,71,Male,2969.6,Yes,No,No,Moderate,Serosa,Bad,1,1,846,Yes
+500,hospital_1,Lev,70,Male,2968,No,No,No,NA,Serosa,Good,3,0,2203,No
+501,hospital_2,Lev,66,Male,2964.8,No,No,No,Moderate,Serosa,Bad,1,0,2164,Yes
+502,hospital_3,Lev,71,Female,2963.2,No,No,No,Moderate,Serosa,Bad,NA,1,1273,Yes
+503,hospital_3,Obs,48,Male,2961.6,No,No,No,Poor,Muscle,Bad,1,0,2393,Yes
+504,hospital_4,Lev,55,Female,2960,No,No,No,Moderate,Serosa,Bad,4,1,862,No
+505,hospital_1,Lev,72,Female,2942.4,No,No,No,Poor,Muscle,Good,2,0,2331,Yes
+506,hospital_4,Lev,57,Male,2940.8,No,No,No,NA,Serosa,Good,3,0,2264,Yes
+507,hospital_5,Lev,57,Male,2929.6,No,No,No,Poor,Serosa,Bad,11,1,144,No
+508,hospital_1,Obs,38,Male,2926.4,No,No,No,Well,Serosa,Good,2,0,2429,Yes
+509,hospital_2,Lev,52,Male,2924.8,Yes,No,No,Moderate,Serosa,Bad,0,1,723,Yes
+510,hospital_2,Obs,57,Male,2923.2,No,No,No,Moderate,Serosa,Good,1,0,2530,Yes
+511,hospital_4,Lev,33,Female,2923.2,No,No,No,Moderate,Serosa,Bad,2,1,1568,No
+512,hospital_1,Obs,39,Female,2916.8,No,No,No,Moderate,Muscle,Good,2,0,2292,Yes
+513,hospital_2,Lev,61,Male,2916.8,No,No,No,Moderate,Serosa,Good,1,0,2252,Yes
+514,hospital_1,Lev,71,Female,2912,No,No,No,Poor,Serosa,Good,1,0,2408,No
+515,hospital_3,Lev,58,Male,2910.4,No,No,No,Moderate,Serosa,Good,4,0,2555,No
+516,hospital_3,Lev,66,Female,2908.8,No,No,No,Poor,Serosa,Bad,7,1,276,Yes
+517,hospital_3,Obs,59,Female,2902.4,No,No,No,Moderate,Muscle,Good,4,1,1896,Yes
+518,hospital_3,Lev,43,Female,2902.4,Yes,No,No,Moderate,Serosa,Good,1,0,2147,Yes
+519,hospital_3,Obs,66,Male,2899.2,No,No,No,Moderate,Serosa,Good,3,0,2269,No
+520,hospital_3,Obs,48,Female,2884.8,No,No,No,Moderate,Serosa,Good,1,0,2391,Yes
+521,hospital_5,Lev,68,Male,2880,No,No,No,Moderate,Serosa,Bad,1,1,1424,Yes
+522,hospital_2,Obs,72,Female,2876.8,No,No,No,Moderate,Serosa,Good,NA,0,2257,Yes
+523,hospital_3,Lev,77,Female,2867.2,NA,No,No,Poor,Adjacent structures,Good,10,0,2381,Yes
+524,hospital_1,Lev,68,Female,2864,Yes,No,No,Moderate,Serosa,Good,1,0,2103,Yes
+525,hospital_4,Obs,44,Female,2860.8,No,No,Yes,Moderate,Adjacent structures,Good,1,0,2210,Yes
+526,hospital_1,Lev,63,Female,2852.8,No,No,No,Moderate,Serosa,Good,1,0,2530,No
+527,hospital_1,Lev,66,Male,2835.2,No,No,No,Moderate,Serosa,Good,1,0,2386,Yes
+528,hospital_5,Lev,50,Male,2828.8,No,No,No,Poor,Serosa,Bad,3,1,219,Yes
+529,hospital_3,Lev,72,Male,2827.2,No,No,No,Moderate,Serosa,Bad,1,1,486,No
+530,hospital_4,Lev,40,Male,2803.2,No,No,No,Well,Serosa,Bad,5,1,1246,Yes
+531,hospital_4,Lev,49,Male,2792,No,No,No,Moderate,Serosa,Good,10,0,2138,Yes
+532,hospital_1,Lev,56,Female,2756.8,No,No,No,Poor,Serosa,Good,2,0,2439,No
+533,hospital_4,Obs,61,Male,2734.4,No,No,No,Moderate,Muscle,Good,2,0,2231,Yes
+534,hospital_5,Obs,65,Male,2707.2,No,No,No,Moderate,Serosa,Bad,6,1,384,Yes
+535,hospital_3,Lev,65,Male,2686.4,No,No,No,Moderate,Muscle,Good,2,0,2505,Yes
+536,hospital_5,Lev,72,Female,2673.6,No,No,No,Well,Submucosa,Bad,1,1,1652,Yes
+537,hospital_1,Lev,68,Female,2668.8,No,No,Yes,Moderate,Serosa,Good,1,0,2441,No
+538,hospital_4,Obs,59,Female,2649.6,No,No,No,Moderate,Serosa,Bad,4,1,687,No
+539,hospital_4,Lev,59,Male,2643.2,No,No,No,Moderate,Serosa,Good,4,0,2179,Yes
+540,hospital_2,Lev,71,Female,2619.2,Yes,No,No,Moderate,Serosa,Good,6,0,2189,Yes
+541,hospital_3,Lev,49,Male,2592,No,No,No,Moderate,Serosa,Good,8,0,2472,Yes
+542,hospital_1,Lev,70,Male,2571.2,No,No,No,Moderate,Serosa,Good,3,0,2111,Yes
+543,hospital_3,Lev,55,Male,2508.8,No,No,No,Poor,Serosa,Good,7,0,2020,Yes
+544,hospital_4,Lev,46,Female,2480,No,Yes,No,Moderate,Serosa,Bad,7,1,1161,Yes
+545,hospital_1,Obs,77,Male,2476.8,No,No,No,Moderate,Serosa,Good,1,0,2231,Yes
+546,hospital_2,Lev,57,Male,2476.8,No,No,No,Moderate,Serosa,Good,4,0,2300,Yes
+547,hospital_3,Obs,68,Male,2464,No,No,No,Moderate,Serosa,Good,1,0,2391,Yes
+548,hospital_2,Lev,62,Male,2459.2,No,No,Yes,Moderate,Serosa,Bad,1,1,759,No
+549,hospital_2,Obs,44,Male,2448,No,No,No,Poor,Serosa,Bad,7,1,166,No
+550,hospital_1,Lev,58,Female,2433.6,No,No,Yes,Moderate,Serosa,Good,1,0,2323,Yes
+551,hospital_3,Lev,75,Female,2417.6,No,No,No,Well,Serosa,Good,2,0,2321,Yes
+552,hospital_1,Obs,70,Female,2414.4,Yes,No,No,Moderate,Serosa,Good,7,0,1976,Yes
+553,hospital_4,Obs,82,Male,2392,No,No,No,Moderate,Serosa,Good,6,0,2229,No
+554,hospital_3,Lev,61,Female,2371.2,No,No,No,Moderate,Serosa,Bad,3,1,1671,Yes
+555,hospital_2,Obs,52,Male,2358.4,No,No,No,Moderate,Serosa,Good,2,1,1907,Yes
+556,hospital_4,Lev,47,Male,2315.2,No,No,No,Poor,Serosa,Bad,7,1,1783,Yes
+557,hospital_4,Lev,61,Female,2313.6,No,No,No,Poor,Serosa,Bad,7,1,684,Yes
+558,hospital_3,Lev,39,Male,2302.4,No,No,No,Moderate,Serosa,Bad,9,1,441,Yes
+559,hospital_2,Lev,69,Female,2299.2,No,No,No,Moderate,Muscle,Bad,3,1,902,No
+560,hospital_4,Lev,55,Male,2294.4,No,No,No,Poor,Serosa,Good,7,0,2244,Yes
+561,hospital_1,Obs,56,Female,2294.4,Yes,No,No,Moderate,Serosa,Good,1,0,2170,Yes
+562,hospital_3,Obs,80,Male,2278.4,No,No,No,Poor,Serosa,Good,1,0,1870,No
+563,hospital_3,Lev,43,Male,2273.6,No,No,No,Moderate,Serosa,Good,4,0,2066,No
+564,hospital_4,Lev,83,Male,2248,No,No,No,Moderate,Serosa,Good,2,0,2030,Yes
+565,hospital_4,Obs,85,Female,2238.4,No,No,No,Well,Serosa,Bad,1,1,253,Yes
+566,hospital_1,Lev,61,Male,2220.8,No,No,No,Moderate,Serosa,Good,1,0,2047,No
+567,hospital_3,Lev,47,Female,2219.2,No,No,No,Moderate,Adjacent structures,Bad,9,1,1768,Yes
+568,hospital_4,Lev,76,Female,2200,No,No,No,Moderate,Serosa,Good,1,0,2043,Yes
+569,hospital_2,Lev,58,Male,2184,No,No,No,Moderate,Serosa,Good,1,0,2162,Yes
+570,hospital_1,Obs,59,Male,2180.8,No,No,No,Moderate,Muscle,Good,2,0,2093,Yes
+571,hospital_4,Lev,60,Female,2123.2,No,No,No,Moderate,Serosa,Good,1,0,2310,No
+572,hospital_4,Lev,32,Male,2120,No,No,No,Moderate,Serosa,Good,2,1,2128,No
+573,hospital_5,Obs,56,Male,2102.4,No,No,No,NA,Adjacent structures,Good,1,1,1884,No
+574,hospital_5,Lev,75,Male,2100.8,No,No,No,Moderate,Serosa,Bad,2,1,219,No
+575,hospital_4,Lev,62,Male,2089.6,No,No,No,Well,Serosa,Good,3,0,2309,No
+576,hospital_4,Obs,69,Female,2086.4,No,No,No,Moderate,Serosa,Bad,12,1,313,Yes
+577,hospital_5,Lev,72,Male,2083.2,No,No,Yes,Moderate,Serosa,Bad,4,1,546,Yes
+578,hospital_2,Obs,54,Female,2072,No,No,No,Moderate,Serosa,Good,1,1,2213,Yes
+579,hospital_5,Lev,72,Male,2072,No,No,No,Moderate,Serosa,Good,1,1,1856,No
+580,hospital_2,Lev,27,Female,2064,No,No,No,Moderate,Serosa,NA,1,0,1421,No
+581,hospital_4,Lev,62,Female,2046.4,No,No,No,Moderate,Adjacent structures,Bad,4,1,460,Yes
+582,hospital_1,Lev,39,Female,2046.4,No,No,No,Moderate,Submucosa,Good,2,0,2173,No
+583,hospital_5,Lev,60,Female,2041.6,No,No,No,Moderate,Serosa,Bad,4,1,283,Yes
+584,hospital_2,Lev,55,Male,2041.6,Yes,No,No,Poor,Serosa,Bad,5,1,34,Yes
+585,hospital_1,Obs,64,Male,2036.8,No,No,No,Moderate,Serosa,Good,1,0,2191,Yes
+586,hospital_3,Lev,68,Female,2035.2,No,No,No,Poor,Serosa,Good,12,0,2186,No
+587,hospital_3,Obs,65,Female,2019.2,No,No,No,Moderate,Serosa,Bad,2,1,1159,Yes
+588,hospital_4,Lev,66,Female,2019.2,Yes,No,No,Well,Serosa,Bad,3,1,616,Yes
+589,hospital_1,Lev,39,Male,2003.2,No,No,No,Poor,Serosa,Good,2,0,2270,Yes
+590,hospital_1,Lev,54,Male,1993.6,No,No,Yes,Moderate,Serosa,Bad,NA,1,1061,No
+591,hospital_5,Obs,34,Male,1993.6,Yes,No,No,Moderate,Serosa,Bad,1,1,591,No
+592,hospital_4,Lev,74,Female,1979.2,No,No,No,Moderate,Serosa,Good,4,0,2065,Yes
+593,hospital_2,Obs,81,Female,1968,Yes,No,Yes,Moderate,Serosa,Bad,3,1,208,Yes
+594,hospital_1,Lev,38,Male,1950.4,No,No,No,Moderate,Serosa,Good,1,0,2360,Yes
+595,hospital_2,Lev,59,Female,1945.6,No,No,No,Moderate,Serosa,Good,3,0,2312,Yes
+596,hospital_2,Lev,62,Female,1944,No,No,No,Moderate,Serosa,Good,1,0,1902,Yes
+597,hospital_2,Lev,61,Male,1939.2,Yes,No,No,Well,Muscle,NA,5,0,1814,Yes
+598,hospital_1,Obs,46,Male,1934.4,Yes,No,No,Moderate,Serosa,Good,2,0,2111,No
+599,hospital_1,Lev,55,Male,1931.2,No,No,No,Moderate,Serosa,Good,1,0,2330,Yes
+600,hospital_4,Obs,57,Male,1921.6,No,No,No,Moderate,Serosa,Good,5,0,2202,Yes
+601,hospital_4,Lev,38,Female,1916.8,No,No,No,Moderate,Serosa,Bad,3,1,1295,No
+602,hospital_5,Lev,69,Female,1912,No,No,Yes,Moderate,Serosa,Good,19,0,1918,Yes
+603,hospital_4,Obs,79,Female,1908.8,No,No,Yes,Moderate,Muscle,Good,6,0,2066,Yes
+604,hospital_4,Lev,71,Female,1905.6,No,No,No,Moderate,Serosa,Good,2,0,2136,No
+605,hospital_2,Lev,74,Male,1897.6,No,No,No,Poor,Serosa,Good,1,0,2289,Yes
+606,hospital_4,Lev,30,Female,1884.8,Yes,No,No,Moderate,Serosa,Bad,12,1,576,Yes
+607,hospital_1,Obs,72,Female,1884.8,No,No,No,Poor,Serosa,Good,1,0,2232,Yes
+608,hospital_5,Lev,68,Female,1865.6,NA,No,No,Moderate,Serosa,Bad,3,1,1034,Yes
+609,hospital_2,Lev,66,Male,1857.6,Yes,No,No,Poor,Submucosa,Bad,NA,1,583,Yes
+610,hospital_5,Obs,63,Male,1854.4,No,No,No,Moderate,Serosa,Bad,4,1,417,Yes
+611,hospital_3,Lev,52,Female,1846.4,No,No,Yes,Moderate,Serosa,Good,1,0,1905,Yes
+612,hospital_4,Lev,64,Male,1841.6,No,No,No,Moderate,Serosa,Bad,4,1,875,Yes
+613,hospital_5,Lev,68,Male,1832,No,No,No,Moderate,Serosa,Bad,1,1,674,Yes
+614,hospital_3,Lev,74,Male,1832,No,No,No,Moderate,Serosa,Good,2,0,2185,Yes
+615,hospital_5,Lev,32,Male,1822.4,No,No,No,Moderate,Serosa,Bad,2,1,1151,No
+616,hospital_4,Lev,60,Female,1820.8,Yes,No,No,Moderate,Serosa,Bad,6,1,342,Yes
+617,hospital_5,Obs,39,Female,1817.6,No,No,No,Moderate,Serosa,Good,8,0,2187,Yes
+618,hospital_5,Obs,76,Female,1816,No,No,Yes,Moderate,Serosa,Bad,5,1,1434,Yes
+619,hospital_5,Lev,62,Male,1814.4,No,No,No,Poor,Serosa,Bad,14,1,430,Yes
+620,hospital_4,Lev,41,Female,1812.8,No,No,Yes,Moderate,Serosa,Good,2,0,2339,Yes
+621,hospital_5,Lev,35,Male,1795.2,No,No,Yes,Moderate,Serosa,Bad,2,1,1365,Yes
+622,hospital_4,Obs,59,Female,1787.2,No,No,No,Moderate,Serosa,Good,1,0,2313,No
+623,hospital_3,Obs,52,Male,1779.2,No,No,No,Moderate,Serosa,Good,2,0,2153,Yes
+624,hospital_2,Lev,65,Male,1768,No,No,No,Moderate,Serosa,Good,1,0,2164,No
+625,hospital_3,Lev,61,Male,1764.8,No,No,No,Poor,Serosa,Good,3,0,2180,No
+626,hospital_4,Obs,61,Male,1761.6,No,No,No,Well,Serosa,Good,8,0,2110,Yes
+627,hospital_1,Obs,59,Male,1747.2,No,No,No,Well,Serosa,Good,1,0,2139,Yes
+628,hospital_1,Lev,59,Male,1732.8,No,No,No,NA,Serosa,Good,2,0,2120,No
+629,hospital_3,Lev,71,Female,1726.4,No,No,No,Moderate,Muscle,Good,5,1,2197,Yes
+630,hospital_2,Obs,39,Male,1712,No,No,No,Poor,Adjacent structures,NA,4,0,453,No
+631,hospital_4,Obs,65,Male,1697.6,No,No,No,Poor,Serosa,Bad,7,1,928,No
+632,hospital_2,Lev,34,Female,1688,Yes,No,No,Well,Serosa,Bad,3,1,675,Yes
+633,hospital_1,Obs,51,Male,1676.8,Yes,No,No,Moderate,Serosa,Good,4,0,2170,No
+634,hospital_3,Obs,55,Female,1673.6,No,No,No,Moderate,Serosa,Good,3,0,2138,Yes
+635,hospital_4,Lev,65,Male,1665.6,No,Yes,No,Poor,Serosa,Good,3,0,2255,Yes
+636,hospital_1,Lev,71,Female,1659.2,No,No,No,Well,Serosa,Good,NA,0,2290,No
+637,hospital_2,Lev,68,Female,1654.4,Yes,No,No,Moderate,Serosa,Bad,1,1,1055,Yes
+638,hospital_2,Lev,59,Female,1649.6,No,No,No,Moderate,Serosa,Good,1,0,2347,No
+639,hospital_4,Lev,66,Male,1635.2,No,No,No,Poor,Serosa,Bad,2,1,573,No
+640,hospital_4,Obs,62,Male,1633.6,No,No,No,Moderate,Muscle,Good,2,0,2200,No
+641,hospital_5,Lev,40,Female,1628.8,No,No,No,Moderate,Serosa,Bad,8,1,550,Yes
+642,hospital_5,Lev,64,Male,1595.2,No,No,No,Poor,Serosa,Bad,3,1,1405,Yes
+643,hospital_4,Lev,40,Male,1595.2,Yes,No,No,Poor,Serosa,Good,2,0,2355,No
+644,hospital_4,Lev,70,Male,1588.8,No,No,No,Moderate,Serosa,Bad,9,1,1186,Yes
+645,hospital_2,Lev,66,Male,1577.6,No,No,Yes,NA,Adjacent structures,Bad,1,1,1540,Yes
+646,hospital_3,Lev,73,Male,1563.2,Yes,No,Yes,Moderate,Muscle,Good,1,0,2229,Yes
+647,hospital_3,Lev,69,Male,1561.6,No,No,No,Well,Serosa,Bad,1,1,969,Yes
+648,hospital_3,Obs,58,Male,1550.4,No,No,No,Moderate,Serosa,Bad,1,1,465,Yes
+649,hospital_4,Lev,55,Female,1548.8,No,No,No,Moderate,Serosa,Bad,6,1,603,No
+650,hospital_5,Lev,53,Female,1545.6,No,No,Yes,Moderate,Serosa,Bad,6,1,997,No
+651,hospital_1,Lev,52,Male,1540.8,No,No,No,Moderate,Serosa,Good,2,0,2274,Yes
+652,hospital_3,Obs,62,Female,1537.6,No,No,No,Moderate,Serosa,Bad,3,1,563,Yes
+653,hospital_3,Lev,61,Male,1537.6,No,No,Yes,Moderate,Serosa,Bad,2,1,1434,Yes
+654,hospital_4,Lev,69,Female,1537.6,No,No,No,Moderate,Serosa,Good,3,0,2316,Yes
+655,hospital_5,Lev,41,Female,1537.6,Yes,No,No,Moderate,Serosa,Bad,3,1,692,Yes
+656,hospital_5,Obs,64,Male,1531.2,No,No,No,Moderate,Serosa,Bad,3,1,1447,No
+657,hospital_5,Lev,59,Female,1523.2,No,No,No,Poor,Serosa,Bad,3,1,428,Yes
+658,hospital_2,Lev,65,Female,1518.4,No,No,No,Well,Muscle,Good,1,0,2152,Yes
+659,hospital_4,Obs,66,Male,1510.4,No,No,No,Moderate,Serosa,Bad,3,1,854,Yes
+660,hospital_1,Lev,60,Male,1507.2,No,No,No,Moderate,Serosa,Good,2,0,2093,Yes
+661,hospital_2,Lev,43,Male,1504,No,No,Yes,Moderate,Serosa,Good,1,0,2198,No
+662,hospital_2,Obs,74,Male,1502.4,No,No,No,Poor,Serosa,Good,1,0,2126,Yes
+663,hospital_1,Lev,67,Male,1500.8,No,No,No,Poor,Muscle,Good,2,0,2189,Yes
+664,hospital_1,Lev,46,Male,1497.6,Yes,No,No,Moderate,Serosa,Good,1,0,2142,Yes
+665,hospital_2,Lev,47,Male,1486.4,No,No,No,Moderate,Muscle,Good,3,0,2278,Yes
+666,hospital_3,Obs,66,Male,1484.8,Yes,No,No,Moderate,Serosa,Bad,4,1,622,Yes
+667,hospital_2,Lev,36,Female,1478.4,Yes,No,No,Moderate,Serosa,Good,6,0,2192,Yes
+668,hospital_3,Obs,62,Male,1465.6,Yes,No,No,Poor,Serosa,Bad,2,1,413,No
+669,hospital_5,Lev,69,Female,1457.6,No,No,No,Moderate,Serosa,Bad,2,1,1191,Yes
+670,hospital_3,Obs,76,Female,1454.4,No,No,No,Well,Serosa,Bad,3,1,1139,Yes
+671,hospital_5,Lev,36,Male,1448,Yes,No,No,Poor,Serosa,Bad,2,1,165,Yes
+672,hospital_1,Obs,73,Male,1448,No,No,Yes,NA,Muscle,Good,3,0,2210,Yes
+673,hospital_3,Obs,72,Male,1443.2,No,No,No,Moderate,Muscle,Good,5,0,2227,Yes
+674,hospital_4,Lev,61,Male,1441.6,No,No,No,Moderate,Muscle,Good,1,0,2076,No
+675,hospital_1,Obs,58,Male,1424,No,No,No,Moderate,Serosa,Good,2,0,2132,Yes
+676,hospital_2,Lev,52,Female,1419.2,Yes,No,No,Well,Serosa,Good,3,0,2084,Yes
+677,hospital_3,Obs,66,Male,1419.2,No,No,No,Moderate,Adjacent structures,Good,2,0,1905,No
+678,hospital_3,Lev,43,Female,1419.2,No,No,No,Moderate,Serosa,Bad,7,1,608,Yes
+679,hospital_1,Lev,60,Male,1416,No,No,No,Moderate,Muscle,Good,1,0,2066,Yes
+680,hospital_3,Obs,61,Female,1414.4,No,No,No,Moderate,Serosa,Good,4,0,2006,Yes
+681,hospital_4,Lev,61,Male,1412.8,No,No,No,Moderate,Muscle,Good,3,0,2183,Yes
+682,hospital_2,Lev,46,Male,1400,No,No,No,Moderate,Submucosa,Good,1,0,2099,Yes
+683,hospital_3,Lev,73,Male,1398.4,No,No,No,Moderate,Serosa,Good,1,0,1879,Yes
+684,hospital_4,Obs,65,Female,1380.8,Yes,No,No,Moderate,Serosa,Bad,3,1,264,Yes
+685,hospital_2,Lev,61,Female,1379.2,Yes,No,No,Moderate,Serosa,Good,1,0,2107,No
+686,hospital_5,Lev,65,Male,1372.8,No,No,No,Poor,Serosa,Bad,15,1,743,No
+687,hospital_3,Obs,68,Male,1366.4,No,No,No,Moderate,Serosa,Bad,2,1,966,Yes
+688,hospital_4,Lev,63,Male,1353.6,No,No,No,Moderate,Serosa,Good,1,0,2076,Yes
+689,hospital_5,Lev,72,Male,1352,Yes,No,No,Poor,Serosa,Bad,4,1,24,No
+690,hospital_4,Lev,74,Female,1350.4,No,Yes,No,Moderate,Serosa,Bad,2,1,448,Yes
+691,hospital_5,Lev,45,Female,1344,No,No,No,Moderate,Serosa,Bad,9,1,909,Yes
+692,hospital_3,Lev,66,Female,1332.8,No,No,No,Well,Serosa,Good,1,0,2188,No
+693,hospital_3,Obs,38,Male,1332.8,NA,No,No,NA,Adjacent structures,Bad,2,1,469,Yes
+694,hospital_2,Obs,46,Female,1331.2,No,Yes,Yes,Poor,Adjacent structures,Bad,2,1,594,Yes
+695,hospital_1,Lev,51,Female,1297.6,No,No,No,Moderate,Serosa,Good,1,0,2008,Yes
+696,hospital_2,Lev,65,Male,1289.6,No,No,No,Moderate,Adjacent structures,Bad,3,1,1276,No
+697,hospital_3,Obs,55,Male,1289.6,No,No,No,Moderate,Serosa,Bad,2,1,957,Yes
+698,hospital_4,Obs,58,Male,1283.2,No,No,No,Moderate,Serosa,Good,4,1,1950,Yes
+699,hospital_1,Lev,65,Male,1283.2,No,No,No,Moderate,Serosa,Good,1,0,2668,No
+700,hospital_1,Lev,46,Female,1275.2,Yes,No,No,Well,Serosa,Good,2,0,2250,Yes
+701,hospital_1,Lev,57,Female,1272,No,No,No,Moderate,Serosa,Good,1,0,2191,Yes
+702,hospital_2,Obs,67,Male,1240,No,No,Yes,Moderate,Serosa,Good,1,0,2365,Yes
+703,hospital_1,Lev,75,Female,1238.4,No,No,No,Moderate,Serosa,Good,1,0,2331,Yes
+704,hospital_5,Lev,64,Male,1232,No,No,Yes,Moderate,Serosa,Bad,5,1,1262,Yes
+705,hospital_2,Lev,63,Male,1225.6,No,No,No,Moderate,Serosa,NA,2,0,1537,Yes
+706,hospital_1,Lev,64,Male,1224,No,No,No,Moderate,Serosa,Good,3,0,2387,No
+707,hospital_1,Obs,59,Male,1222.4,No,No,No,Moderate,Serosa,Bad,1,0,2235,Yes
+708,hospital_3,Lev,78,Female,1217.6,No,No,No,Moderate,Serosa,Bad,3,0,1980,Yes
+709,hospital_4,Lev,63,Male,1216,No,No,No,Well,Submucosa,Bad,2,1,578,Yes
+710,hospital_3,Obs,57,Male,1214.4,No,No,No,Well,Serosa,Bad,4,1,1083,Yes
+711,hospital_5,Obs,52,Male,1214.4,No,No,No,Moderate,Serosa,Good,3,1,1875,No
+712,hospital_1,Obs,50,Female,1212.8,No,No,No,Moderate,Serosa,Good,3,0,2384,No
+713,hospital_2,Obs,36,Male,1208,Yes,No,No,Moderate,Serosa,Bad,3,1,563,Yes
+714,hospital_1,Lev,50,Female,1204.8,No,No,No,Poor,Serosa,Good,4,0,2076,Yes
+715,hospital_1,Obs,53,Male,1188.8,No,No,No,Moderate,Serosa,Good,1,0,2025,Yes
+716,hospital_4,Lev,48,Male,1188.8,No,No,No,Moderate,Serosa,Good,7,0,2055,Yes
+717,hospital_3,Obs,55,Female,1182.4,No,No,No,Moderate,Serosa,Bad,2,1,1375,No
+718,hospital_2,Lev,47,Male,1177.6,No,No,No,Moderate,Muscle,Good,2,0,2350,Yes
+719,hospital_1,Lev,74,Female,1168,No,No,Yes,Moderate,Serosa,Good,1,0,2200,Yes
+720,hospital_3,Lev,53,Male,1166.4,Yes,Yes,No,Moderate,Serosa,Good,3,0,2222,Yes
+721,hospital_2,Obs,55,Male,1156.8,No,No,No,Moderate,Serosa,Good,7,0,2149,Yes
+722,hospital_3,Lev,53,Male,1153.6,No,No,No,Moderate,Muscle,Good,4,0,2303,No
+723,hospital_3,Obs,67,Male,1152,No,Yes,No,Moderate,Adjacent structures,Bad,4,1,322,Yes
+724,hospital_5,Lev,56,Male,1148.8,No,No,No,Moderate,Serosa,Bad,3,1,764,Yes
+725,hospital_3,Lev,30,Female,1147.2,Yes,No,Yes,Moderate,Serosa,Bad,1,1,765,Yes
+726,hospital_5,Lev,56,Female,1145.6,No,No,No,Well,Serosa,Bad,8,1,93,No
+727,hospital_1,Lev,46,Male,1139.2,Yes,No,No,Moderate,Serosa,Good,3,0,1918,Yes
+728,hospital_4,Lev,60,Male,1134.4,No,No,No,Well,Muscle,Good,1,1,1932,Yes
+729,hospital_1,Obs,60,Female,1134.4,No,No,No,Moderate,Muscle,Good,1,0,2278,No
+730,hospital_5,Obs,57,Male,1132.8,Yes,No,No,Poor,Serosa,Bad,9,1,145,Yes
+731,hospital_1,Lev,42,Female,1129.6,No,No,No,Poor,Serosa,Good,1,0,1913,Yes
+732,hospital_2,Obs,58,Male,1113.6,No,No,No,Moderate,Serosa,Good,2,0,2176,Yes
+733,hospital_3,Obs,53,Female,1108.8,No,No,No,Poor,Serosa,Good,1,0,1995,No
+734,hospital_4,Lev,73,Male,1107.2,No,No,Yes,Moderate,Serosa,Good,1,0,2023,Yes
+735,hospital_2,Obs,73,Male,1107.2,No,No,No,Moderate,Serosa,Good,7,0,1935,Yes
+736,hospital_2,Obs,57,Male,1107.2,No,No,No,Moderate,Serosa,Good,NA,0,2191,No
+737,hospital_2,Lev,77,Female,1099.2,No,No,No,Poor,Serosa,Good,1,0,2191,No
+738,hospital_1,Obs,60,Male,1096,No,No,No,NA,Serosa,Good,2,0,1856,Yes
+739,hospital_4,Lev,74,Male,1094.4,No,No,No,Moderate,Serosa,Bad,8,1,628,Yes
+740,hospital_2,Lev,70,Male,1084.8,No,No,No,Moderate,Muscle,Good,3,0,1976,Yes
+741,hospital_1,Obs,53,Female,1080,No,No,No,Moderate,Serosa,NA,5,0,1819,No
+742,hospital_4,Lev,68,Female,1078.4,No,No,Yes,Moderate,Adjacent structures,Bad,8,1,141,Yes
+743,hospital_4,Lev,59,Male,1076.8,Yes,No,No,Moderate,Serosa,Bad,2,1,422,Yes
+744,hospital_3,Lev,29,Male,1072,Yes,No,No,Moderate,Serosa,Good,3,0,2006,Yes
+745,hospital_1,Obs,57,Female,1070.4,No,No,No,Moderate,Muscle,Good,2,0,2113,Yes
+746,hospital_3,Obs,61,Male,1065.6,No,No,No,Moderate,Muscle,NA,4,0,1823,Yes
+747,hospital_2,Obs,68,Male,1064,Yes,No,No,Moderate,Serosa,Good,3,0,2170,Yes
+748,hospital_3,Lev,49,Male,1062.4,No,No,No,Moderate,Serosa,Bad,11,1,1812,No
+749,hospital_1,Lev,70,Female,1060.8,No,No,No,Moderate,Serosa,Good,2,0,1838,Yes
+750,hospital_1,Obs,53,Male,1054.4,Yes,No,No,Moderate,Serosa,Good,2,0,1855,Yes
+751,hospital_2,Lev,57,Female,1035.2,Yes,No,No,Poor,Serosa,Bad,2,1,269,No
+752,hospital_2,Lev,76,Male,1028.8,No,No,No,Moderate,Serosa,Good,1,0,2414,Yes
+753,hospital_2,Lev,59,Male,1028.8,No,No,Yes,Moderate,Muscle,Good,2,0,2174,Yes
+754,hospital_3,Lev,56,Male,1027.2,No,No,No,Moderate,Muscle,Good,1,0,2263,No
+755,hospital_4,Lev,38,Male,1027.2,No,No,No,Moderate,Serosa,Bad,7,1,1495,Yes
+756,hospital_4,Lev,61,Female,1025.6,No,No,No,Poor,Serosa,Bad,10,1,314,Yes
+757,hospital_3,Obs,49,Male,1006.4,No,No,No,Moderate,Serosa,Good,2,0,2261,Yes
+758,hospital_5,Obs,69,Female,1004.8,No,No,No,Moderate,Serosa,Bad,12,1,716,Yes
+759,hospital_3,Obs,53,Male,995.2,No,No,No,Moderate,Serosa,Good,1,0,2190,No
+760,hospital_2,Lev,72,Female,985.6,No,No,No,Poor,Serosa,Good,6,0,2331,No
+761,hospital_1,Lev,57,Female,982.4,No,No,No,Moderate,Serosa,Good,3,0,2187,Yes
+762,hospital_5,Lev,73,Male,979.2,No,No,Yes,Moderate,Adjacent structures,Bad,1,1,602,Yes
+763,hospital_4,Lev,58,Female,974.4,No,No,Yes,Well,Serosa,Bad,2,1,666,Yes
+764,hospital_5,Lev,69,Male,972.8,No,No,No,Moderate,Serosa,Bad,5,1,138,Yes
+765,hospital_1,Obs,69,Female,964.8,Yes,No,No,Poor,Serosa,Good,3,0,2001,Yes
+766,hospital_5,Lev,47,Female,963.2,No,No,No,Moderate,Serosa,Bad,5,1,887,Yes
+767,hospital_2,Lev,80,Female,963.2,No,Yes,No,Well,Muscle,Bad,2,1,1207,Yes
+768,hospital_1,Lev,67,Male,961.6,No,No,No,Moderate,Serosa,Good,2,0,1997,Yes
+769,hospital_1,Lev,54,Female,958.4,No,No,No,Moderate,Serosa,Good,1,0,1864,Yes
+770,hospital_3,Lev,63,Male,952,NA,No,Yes,Poor,Serosa,Good,7,0,2422,No
+771,hospital_4,Lev,65,Female,950.4,Yes,No,No,Poor,Serosa,Bad,NA,1,444,No
+772,hospital_4,Lev,65,Female,947.2,No,Yes,Yes,Moderate,Serosa,Good,3,0,2375,Yes
+773,hospital_5,Obs,48,Female,945.6,Yes,No,No,Moderate,Serosa,Bad,2,1,718,Yes
+774,hospital_1,Obs,52,Male,942.4,No,No,No,Moderate,Serosa,Good,2,0,2204,Yes
+775,hospital_1,Obs,67,Male,939.2,No,No,Yes,Well,Serosa,Good,1,0,2120,No
+776,hospital_5,Lev,70,Female,932.8,No,Yes,Yes,Well,Serosa,Bad,5,1,766,Yes
+777,hospital_5,Lev,51,Female,931.2,Yes,No,Yes,Poor,Serosa,Bad,6,1,366,Yes
+778,hospital_5,Lev,32,Female,928,No,No,No,Poor,Muscle,Bad,14,1,1752,Yes
+779,hospital_1,Lev,63,Male,928,No,No,Yes,Poor,Serosa,Good,7,0,2183,Yes
+780,hospital_1,Obs,81,Female,924.8,No,No,Yes,Moderate,Serosa,Good,1,0,1902,Yes
+781,hospital_3,Obs,66,Male,921.6,No,No,No,Moderate,Adjacent structures,Bad,7,1,259,No
+782,hospital_4,Lev,60,Female,921.6,No,Yes,Yes,Poor,Serosa,Bad,4,1,609,Yes
+783,hospital_5,Obs,81,Female,916.8,Yes,No,No,Well,Serosa,Bad,1,1,832,Yes
+784,hospital_2,Obs,66,Male,912,Yes,No,Yes,Moderate,Serosa,Bad,4,1,164,No
+785,hospital_2,Lev,78,Male,910.4,No,No,Yes,Poor,Serosa,Good,2,0,1828,No
+786,hospital_2,Lev,46,Female,900.8,No,No,No,Moderate,Serosa,Good,3,0,2147,Yes
+787,hospital_4,Obs,57,Female,900.8,No,No,No,Moderate,Serosa,Bad,NA,1,201,Yes
+788,hospital_1,Lev,57,Female,894.4,No,No,No,Moderate,Submucosa,Good,3,0,2221,No
+789,hospital_2,Lev,67,Female,884.8,No,No,No,Poor,Serosa,Bad,2,1,503,Yes
+790,hospital_5,Lev,68,Male,880,No,No,No,Moderate,Serosa,Bad,9,1,376,Yes
+791,hospital_2,Lev,38,Female,873.6,No,No,No,Moderate,Serosa,Bad,2,1,811,Yes
+792,hospital_1,Lev,70,Female,859.2,No,No,No,Moderate,Serosa,Good,3,0,1985,Yes
+793,hospital_1,Obs,66,Male,846.4,No,No,No,Moderate,Serosa,Good,2,0,2076,No
+794,hospital_4,Lev,63,Male,844.8,No,No,No,Moderate,Serosa,Bad,8,1,1154,No
+795,hospital_5,Lev,72,Male,835.2,No,No,No,Moderate,Muscle,Bad,5,1,844,No
+796,hospital_2,Obs,61,Male,819.2,Yes,No,Yes,Well,Serosa,Bad,1,1,1031,No
+797,hospital_5,Lev,46,Male,816,No,No,No,Moderate,Serosa,Bad,3,1,1302,No
+798,hospital_2,Lev,36,Female,809.6,Yes,No,No,Moderate,Serosa,Good,3,0,2169,Yes
+799,hospital_2,Obs,69,Female,804.8,No,No,No,Moderate,Muscle,Good,1,0,1929,Yes
+800,hospital_2,Lev,75,Female,798.4,No,No,No,Moderate,Serosa,NA,1,0,1800,Yes
+801,hospital_5,Lev,64,Female,798.4,No,No,No,Moderate,Serosa,Bad,12,1,355,No
+802,hospital_1,Lev,77,Male,798.4,No,No,No,Moderate,Serosa,Bad,1,1,669,No
+803,hospital_3,Obs,51,Female,796.8,NA,No,No,Moderate,Muscle,Bad,7,1,465,Yes
+804,hospital_4,Obs,36,Male,784,No,No,No,Moderate,Serosa,Bad,6,0,2157,No
+805,hospital_5,Obs,56,Male,777.6,No,No,No,Moderate,Serosa,Bad,7,1,929,Yes
+806,hospital_3,Lev,63,Female,776,No,No,No,Moderate,Serosa,Good,2,0,2242,Yes
+807,hospital_2,Lev,64,Male,774.4,No,No,No,Moderate,Serosa,Good,2,0,2212,Yes
+808,hospital_1,Lev,44,Male,760,No,No,No,Moderate,Serosa,Good,1,0,2148,No
+809,hospital_5,Lev,73,Male,758.4,Yes,No,No,Moderate,Serosa,Bad,7,1,171,Yes
+810,hospital_3,Lev,54,Male,755.2,Yes,No,No,Moderate,Adjacent structures,Bad,1,1,629,Yes
+811,hospital_2,Lev,44,Male,750.4,No,No,No,Moderate,Muscle,Good,2,1,1829,Yes
+812,hospital_2,Lev,30,Male,744,No,Yes,No,Moderate,Serosa,Good,9,0,1939,No
+813,hospital_5,Lev,65,Female,744,No,No,No,Moderate,Serosa,Bad,7,1,529,No
+814,hospital_2,Obs,68,Female,742.4,Yes,No,No,Moderate,Serosa,Good,2,0,2130,Yes
+815,hospital_1,Obs,56,Female,739.2,No,No,No,NA,Submucosa,Good,2,0,1990,Yes
+816,hospital_3,Obs,62,Male,736,No,No,No,Poor,Serosa,Bad,5,1,587,Yes
+817,hospital_4,Lev,36,Female,734.4,No,No,No,Well,Muscle,Bad,7,1,1145,Yes
+818,hospital_1,Lev,57,Male,726.4,No,No,No,Well,Serosa,Good,2,0,2162,Yes
+819,hospital_5,Lev,31,Male,724.8,Yes,No,No,Well,Serosa,Bad,NA,1,643,Yes
+820,hospital_4,Lev,39,Male,716.8,No,No,No,Moderate,Serosa,Good,11,0,2129,No
+821,hospital_5,Obs,53,Male,710.4,No,No,No,Moderate,Serosa,Bad,3,1,1437,Yes
+822,hospital_5,Lev,60,Male,708.8,Yes,No,No,Moderate,Adjacent structures,Bad,14,1,512,Yes
+823,hospital_1,Obs,65,Female,705.6,Yes,No,No,Moderate,Serosa,Good,1,0,2008,No
+824,hospital_1,Lev,61,Female,702.4,No,No,No,Moderate,Serosa,NA,1,0,1814,Yes
+825,hospital_4,Lev,77,Female,700.8,Yes,No,Yes,Moderate,Serosa,Good,3,0,2161,Yes
+826,hospital_5,Obs,48,Female,700.8,Yes,No,No,Moderate,Serosa,Bad,5,1,506,No
+827,hospital_2,Obs,77,Male,699.2,No,No,No,Well,Serosa,Bad,3,1,1482,Yes
+828,hospital_3,Lev,69,Male,692.8,No,No,No,Poor,Serosa,Good,10,0,1964,Yes
+829,hospital_5,Lev,36,Female,688,No,No,No,Poor,Serosa,Bad,17,1,693,Yes
+830,hospital_3,Lev,64,Female,688,No,No,Yes,Moderate,Serosa,Bad,4,1,592,Yes
+831,hospital_2,Lev,70,Male,684.8,No,No,No,Moderate,Muscle,Good,1,0,2207,Yes
+832,hospital_1,Lev,74,Female,675.2,No,No,No,Well,Serosa,Good,3,0,2181,Yes
+833,hospital_5,Lev,63,Male,673.6,No,No,No,Poor,Serosa,Bad,9,1,696,Yes
+834,hospital_5,Lev,52,Female,672,No,No,No,Poor,Serosa,Bad,10,1,257,Yes
+835,hospital_5,Lev,54,Female,667.2,No,No,No,Moderate,Serosa,Good,3,1,2171,Yes
+836,hospital_4,Lev,54,Female,660.8,Yes,No,No,Moderate,Serosa,Good,4,0,2209,Yes
+837,hospital_5,Lev,41,Female,660.8,Yes,No,No,Well,Serosa,Bad,1,1,1122,No
+838,hospital_5,Obs,61,Female,657.6,No,No,No,Moderate,Serosa,Bad,4,1,936,Yes
+839,hospital_5,Lev,34,Female,654.4,Yes,No,No,Poor,Serosa,Bad,10,1,601,Yes
+840,hospital_1,Obs,59,Female,649.6,Yes,No,No,Moderate,Serosa,Good,3,0,2265,Yes
+841,hospital_1,Lev,57,Female,643.2,No,No,No,Moderate,Serosa,Good,3,0,2198,Yes
+842,hospital_5,Obs,39,Female,640,No,No,No,Moderate,Muscle,Bad,6,1,275,Yes
+843,hospital_3,Obs,74,Male,624,No,No,No,Poor,Serosa,Bad,3,1,1195,Yes
+844,hospital_4,Lev,45,Male,622.4,Yes,No,No,Moderate,Serosa,Good,3,0,2099,No
+845,hospital_1,Lev,66,Female,614.4,No,No,No,Moderate,Serosa,Good,1,0,2165,Yes
+846,hospital_4,Lev,60,Male,614.4,No,No,No,Moderate,Serosa,Good,2,0,2212,No
+847,hospital_5,Lev,73,Male,611.2,No,No,No,Moderate,Serosa,Bad,1,1,355,No
+848,hospital_1,Obs,76,Female,609.6,No,No,No,Poor,Muscle,Good,1,0,2097,Yes
+849,hospital_2,Lev,79,Female,601.6,Yes,No,No,Moderate,Serosa,Bad,1,1,56,Yes
+850,hospital_5,Lev,47,Male,595.2,Yes,No,No,Moderate,Serosa,Bad,4,1,589,No
+851,hospital_5,Obs,60,Male,585.6,No,No,No,Moderate,Serosa,Bad,9,1,510,Yes
+852,hospital_1,Lev,62,Female,584,No,No,No,Moderate,Serosa,Good,3,0,2250,No
+853,hospital_5,Obs,18,Male,580.8,Yes,No,Yes,Poor,Muscle,Bad,4,1,612,No
+854,hospital_4,Lev,75,Female,579.2,No,No,No,Moderate,Serosa,Good,5,0,2284,Yes
+855,hospital_2,Lev,56,Female,569.6,No,No,No,Well,Serosa,Good,3,0,1992,No
+856,hospital_4,Lev,70,Male,568,Yes,No,No,Moderate,Muscle,Bad,5,1,251,Yes
+857,hospital_2,Lev,54,Female,568,No,No,No,NA,Muscle,Good,3,0,2070,Yes
+858,hospital_5,Obs,64,Female,558.4,No,No,No,Moderate,Serosa,Bad,1,1,1209,No
+859,hospital_3,Lev,63,Female,548.8,No,No,No,Moderate,Serosa,Good,1,0,2122,Yes
+860,hospital_3,Lev,52,Female,547.2,Yes,No,No,Well,Serosa,Good,2,0,2111,No
+861,hospital_5,Lev,71,Female,544,No,No,Yes,Moderate,Serosa,Bad,11,1,274,No
+862,hospital_3,Lev,54,Female,529.6,No,No,No,Well,Serosa,Bad,1,1,1306,No
+863,hospital_3,Lev,27,Female,521.6,No,No,No,Poor,Muscle,Bad,1,1,1325,Yes
+864,hospital_2,Obs,68,Male,518.4,No,No,Yes,Moderate,Serosa,Good,10,0,1968,Yes
+865,hospital_4,Obs,49,Female,516.8,No,No,No,Moderate,Serosa,Bad,2,1,753,No
+866,hospital_4,Obs,61,Male,515.2,No,No,Yes,Moderate,Adjacent structures,Bad,2,1,760,Yes
+867,hospital_2,Lev,40,Male,505.6,No,No,No,Moderate,Serosa,Good,16,0,1861,Yes
+868,hospital_5,Lev,38,Male,502.4,No,No,No,Well,Serosa,Bad,3,1,1138,Yes
+869,hospital_1,Obs,56,Female,502.4,No,No,No,Moderate,Muscle,Good,2,0,2167,Yes
+870,hospital_4,Lev,79,Male,500.8,Yes,No,No,Moderate,Serosa,Good,1,0,1944,Yes
+871,hospital_4,Obs,55,Female,497.6,No,No,No,Poor,Serosa,Bad,13,1,372,No
+872,hospital_4,Obs,59,Female,486.4,No,No,No,Moderate,Submucosa,NA,1,0,1792,No
+873,hospital_5,Lev,36,Male,483.2,No,No,Yes,Moderate,Serosa,Bad,4,1,986,Yes
+874,hospital_4,Lev,63,Female,468.8,Yes,No,No,Moderate,Serosa,Good,2,0,2378,Yes
+875,hospital_5,Obs,27,Male,462.4,No,Yes,Yes,Moderate,Serosa,Bad,12,1,390,Yes
+876,hospital_5,Lev,66,Female,452.8,No,No,Yes,Moderate,Muscle,Bad,2,1,642,Yes
+877,hospital_3,Lev,63,Male,452.8,No,No,No,Moderate,Serosa,Good,3,0,2345,Yes
+878,hospital_4,Lev,64,Male,446.4,No,No,No,Moderate,Muscle,Good,2,0,2254,No
+879,hospital_1,Obs,78,Female,441.6,No,No,No,Moderate,Serosa,Good,1,0,2118,Yes
+880,hospital_5,Lev,66,Female,440,Yes,No,No,Moderate,Serosa,Good,2,1,1831,Yes
+881,hospital_2,Obs,64,Female,438.4,No,No,No,Poor,Serosa,Good,3,0,2167,Yes
+882,hospital_4,Obs,68,Male,433.6,No,No,No,Moderate,Serosa,Bad,2,1,1198,Yes
+883,hospital_2,Lev,35,Male,430.4,No,No,Yes,Moderate,Serosa,Good,2,0,2050,No
+884,hospital_4,Lev,64,Male,422.4,No,No,Yes,Poor,Serosa,Bad,2,1,271,Yes
+885,hospital_1,Lev,60,Female,414.4,No,No,No,Moderate,Muscle,Good,2,0,2138,Yes
+886,hospital_3,Obs,55,Female,414.4,Yes,No,No,Moderate,Serosa,Good,1,0,1891,Yes
+887,hospital_5,Obs,39,Male,411.2,No,No,No,Moderate,Serosa,Bad,6,1,1313,Yes
+888,hospital_3,Lev,67,Male,404.8,No,No,No,Moderate,Serosa,Good,3,0,1853,Yes
+889,hospital_1,Lev,55,Male,401.6,Yes,No,No,Poor,Serosa,Good,3,0,2130,Yes
+890,hospital_5,Lev,61,Male,387.2,No,No,No,Moderate,Serosa,Bad,8,1,150,No
+891,hospital_5,Lev,67,Female,385.6,No,No,No,Moderate,Serosa,Bad,6,1,759,Yes
+892,hospital_3,Lev,62,Male,380.8,No,No,No,Moderate,Serosa,Good,1,0,2100,Yes
+893,hospital_1,Lev,52,Female,371.2,No,No,No,Moderate,Serosa,Good,4,0,2101,Yes
+894,hospital_5,Lev,80,Male,361.6,No,No,No,Moderate,Serosa,Bad,1,1,942,Yes
+895,hospital_4,Obs,51,Female,355.2,No,No,No,Moderate,Serosa,NA,11,0,1823,Yes
+896,hospital_5,Obs,74,Male,350.4,No,No,No,Poor,Submucosa,Bad,1,1,665,No
+897,hospital_5,Obs,70,Male,350.4,Yes,Yes,Yes,Moderate,Serosa,Bad,4,1,1656,Yes
+898,hospital_1,Lev,73,Male,348.8,No,No,No,Moderate,Serosa,Good,4,0,1969,Yes
+899,hospital_3,Lev,56,Female,344,No,No,No,Poor,Adjacent structures,Good,3,0,2190,No
+900,hospital_5,Obs,70,Female,332.8,Yes,No,No,Moderate,Serosa,Bad,15,1,576,Yes
+901,hospital_5,Lev,68,Male,329.6,No,No,No,Moderate,Serosa,Bad,12,1,1103,Yes
+902,hospital_5,Lev,51,Male,321.6,No,No,Yes,Poor,Serosa,Bad,2,1,1046,Yes
+903,hospital_1,Lev,56,Female,305.6,No,No,No,Moderate,Serosa,Good,3,0,1929,Yes
+904,hospital_5,Obs,71,Male,299.2,No,No,No,Well,Serosa,Bad,10,1,125,Yes
+905,hospital_2,Obs,63,Female,297.6,No,No,No,Well,Serosa,Bad,2,1,187,Yes
+906,hospital_2,Lev,82,Male,273.6,NA,No,No,Moderate,Serosa,Bad,3,1,939,Yes
+907,hospital_4,Obs,68,Female,273.6,No,No,No,Poor,Serosa,Bad,12,1,887,No
+908,hospital_2,Obs,55,Female,265.6,No,No,No,Moderate,Serosa,NA,2,0,1803,No
+909,hospital_1,Lev,71,Male,264,No,No,No,Moderate,Serosa,Good,1,0,2018,Yes
+910,hospital_5,Lev,68,Female,262.4,No,No,Yes,Moderate,Serosa,Bad,12,1,1509,Yes
+911,hospital_5,Lev,60,Male,240,No,No,No,Moderate,Serosa,Bad,13,1,314,No
+912,hospital_1,Lev,72,Male,232,No,No,No,Well,Serosa,Good,3,0,1971,Yes
+913,hospital_2,Lev,69,Male,230.4,Yes,Yes,Yes,Moderate,Serosa,Good,3,0,1827,Yes
+914,hospital_5,Obs,46,Female,225.6,Yes,No,No,Moderate,Muscle,Bad,3,1,1079,No
+915,hospital_4,Lev,42,Female,220.8,No,No,No,Well,Serosa,Good,6,0,2114,Yes
+916,hospital_5,Obs,37,Female,212.8,No,No,No,Moderate,Serosa,Bad,8,1,1262,Yes
+917,hospital_4,Obs,71,Female,206.4,No,No,No,Poor,Serosa,Bad,5,1,259,Yes
+918,hospital_3,Lev,50,Male,203.2,No,No,No,Moderate,Muscle,Bad,7,1,323,No
+919,hospital_5,Lev,70,Female,200,Yes,No,Yes,Moderate,Muscle,Bad,1,1,678,Yes
+920,hospital_4,Lev,70,Female,195.2,No,No,Yes,Moderate,Muscle,Good,5,0,1827,Yes
+921,hospital_5,Lev,58,Male,180.8,Yes,No,No,Moderate,Adjacent structures,Bad,3,1,1399,No
+922,hospital_4,Lev,70,Female,148.8,No,No,No,Moderate,Serosa,Bad,1,1,1022,Yes
+923,hospital_4,Lev,55,Male,126.4,Yes,No,No,Poor,Serosa,Good,2,0,2240,Yes
+924,hospital_1,Obs,64,Male,89.6,Yes,No,Yes,Poor,Serosa,Good,2,0,2158,Yes
+925,hospital_4,Lev,71,Male,83.2,No,No,Yes,Moderate,Serosa,Good,4,0,1875,Yes
+926,hospital_2,Lev,72,Female,72,No,No,No,Moderate,Serosa,Good,1,0,2154,Yes
+927,hospital_2,Lev,76,Male,54.4,No,No,Yes,Poor,Serosa,Bad,1,1,1018,Yes
+928,hospital_2,Lev,48,Female,38.4,Yes,No,No,Moderate,Serosa,Good,4,0,2072,No
+929,hospital_2,Lev,66,Female,36.8,Yes,No,No,Moderate,Serosa,NA,1,0,1820,Yes
diff --git a/data/cancer.xlsx b/data/cancer.xlsx
new file mode 100644
index 0000000000000000000000000000000000000000..4680846ad2e6891c7436871e37e40a64d7cec393
Binary files /dev/null and b/data/cancer.xlsx differ
diff --git a/radiant-master/DESCRIPTION b/radiant-master/DESCRIPTION
index d4f05fe4133dd3e0be1b4d5b4ce79d106e17e47b..beb0420b5140be589f76885da7cabbc03719d4e6 100644
--- a/radiant-master/DESCRIPTION
+++ b/radiant-master/DESCRIPTION
@@ -14,7 +14,8 @@ Depends:
     radiant.design (>= 1.6.6),
     radiant.basics (>= 1.6.6),
     radiant.model (>= 1.6.6),
-    radiant.multivariate (>= 1.6.6)
+    radiant.multivariate (>= 1.6.6),
+    radiant.quickgen
 Imports:
     shiny (>= 1.8.1),
     import (>= 1.1.0),
diff --git a/radiant-master/inst/app/global.R b/radiant-master/inst/app/global.R
index 58acd78b6e134b0f66c72de57f5ab87d71e97881..1a1e7b7e3d4c90b4930c5ca5342abf0ede9830ee 100644
--- a/radiant-master/inst/app/global.R
+++ b/radiant-master/inst/app/global.R
@@ -42,7 +42,6 @@ source(file.path(getOption("radiant.path.design"), "app/init.R"), encoding = get
 source(file.path(getOption("radiant.path.basics"), "app/init.R"), encoding = getOption("radiant.encoding"), local = TRUE)
 source(file.path(getOption("radiant.path.model"), "app/init.R"), encoding = getOption("radiant.encoding"), local = TRUE)
 source(file.path(getOption("radiant.path.multivariate"), "app/init.R"), encoding = getOption("radiant.encoding"), local = TRUE)
-# 添加quickgen模块的init.R
 source(file.path(getOption("radiant.path.quickgen"), "app/init.R"), encoding = getOption("radiant.encoding"), local = TRUE)
 
 options(radiant.url.patterns = make_url_patterns())
diff --git a/radiant-master/inst/translations/translation_zh.csv b/radiant-master/inst/translations/translation_zh.csv
index d59a979b9b6270d6213059c18f481d9ac91f7169..f4877061a8d59c6965068c215c9e19d19d1e1146 100644
--- a/radiant-master/inst/translations/translation_zh.csv
+++ b/radiant-master/inst/translations/translation_zh.csv
@@ -20,7 +20,7 @@ Sample size:,样本大小：,"clt_ui.R,sampling_ui.R"
 # of samples:,样本数量：,clt_ui.R
 Number of bins:,分箱数量：,"clt_ui.R,visualize_ui.R"
 Central Limit Theorem,中心极限定理,"clt_ui.R,init.R"
-Basics > Probability,基础 > 概率,clt_ui.R
+Basics > Probability,基础统计 > 概率,clt_ui.R
 Please choose a sample size larger than 2,请选择一个大于 2 的样本大小,clt_ui.R
 Please choose 2 or more samples,请选择 2 个或更多样本,clt_ui.R
 Please choose a minimum value for the uniform distribution,请为均匀分布选择一个最小值,clt_ui.R
@@ -61,9 +61,9 @@ Wilcox,Wilcoxon 检验,compare_means_ui.R
 Select plots:,选择绘图类型：,compare_means_ui.R
 Select plots,选择绘图,compare_means_ui.R
 Compare means,均值比较,"compare_means_ui.R,init.R"
-Summary,摘要,"compare_means_ui.R,doe_ui.R, randomizer_ui.R, sample_size_comp.R, sample_size_ui.R, sampling_ui.R,gbt_ui.R,conjoint_ui.R"
-Plot,图形,"compare_means_ui.R,sample_size_comp.R,dtree_ui.R, gbt_ui.R,conjoint_ui.R"
-Basics > Means,基础 > 均值,compare_means_ui.R
+Summary,摘要,"compare_means_ui.R,doe_ui.R, randomizer_ui.R, sample_size_comp.R, sample_size_ui.R, sampling_ui.R,gbt_ui.R,conjoint_ui.R,crtree_ui.R,crs_ui.R"
+Plot,图形,"compare_means_ui.R,sample_size_comp.R,dtree_ui.R, gbt_ui.R,conjoint_ui.R,crtree_ui.R,crs_ui.R"
+Basics > Means,基础统计 > 均值,compare_means_ui.R
 "This analysis requires at least two variables. The first can be of type
 factor, numeric, or interval. The second must be of type numeric or interval.
 If these variable types are not available please select another dataset.
@@ -72,7 +72,7 @@ If these variable types are not available please select another dataset.
 ",compare_means_ui.R
 Nothing to plot. Please select a plot type,没有可绘制的内容，请选择绘图类型,compare_means_ui.R
 Save compare means plot,保存均值比较图,compare_means_ui.R
-Basics > Proportions,基础 > 比例,compare_props_ui.R
+Basics > Proportions,基础统计 > 比例,compare_props_ui.R
 Compare proportions,比较比例,"compare_props_ui.R,init.R"
 "This analysis requires two categorical variables. The first must have
 two or more levels. The second can have only two levels. If these
@@ -88,7 +88,7 @@ Pearson,皮尔逊积矩相关,correlation_ui.R
 Spearman,斯皮尔曼秩相关,correlation_ui.R
 Kendall,肯德尔秩相关,correlation_ui.R
 Calculate correlation,计算相关性,correlation_ui.R
-Basics > Tables,基础 > 表格,correlation_ui.R
+Basics > Tables,基础统计 > 表格,correlation_ui.R
 Correlation,相关性,"correlation_ui.R,init.R"
 Adjust for {factor} variables,针对 {factor} 变量进行调整,"correlation_ui.R,full_factor_ui.R"
 Calculate adjusted p.values,计算调整后的 p 值,correlation_ui.R
@@ -252,7 +252,7 @@ Load data,加载数据,manage_ui.R
 Description,描述,manage_ui.R
 Paste,粘贴,manage_ui.R
 Copy data,复制数据,manage_ui.R
-Save,保存,"manage_ui.R,logistic_ui.R,radiant.R"
+Save,保存,"manage_ui.R,logistic_ui.R,radiant.R,quickgen_ai_ui.R"
 Save data,保存数据,manage_ui.R
 Save radiant state file,保存 Radiant 状态文件,"manage_ui.R,global.R"
 Add/edit data description,添加/编辑数据描述,manage_ui.R
@@ -608,7 +608,7 @@ Estimate model,估计模型,"crs_ui.R, crtree_ui.R, gbt_ui.R, logistic_ui.R,conj
 Re-estimate model,重新估计模型,"crs_ui.R, crtree_ui.R, gbt_ui.R, logistic_ui.R,conjoint_ui.R"
 <label>Store recommendations:</label>,<label>保存推荐结果:</label>,crs_ui.R
 Collaborative Filtering,协同过滤,"crs_ui.R,init.R"
-Model > Recommend,模型 > 推荐,crs_ui.R
+Model > Recommend,模型方法 > 推荐,crs_ui.R
 "This analysis requires a user id, a product id, and product ratings.
 If these variables are not available please select another dataset.
 
@@ -675,7 +675,7 @@ Save decision tree plot,保存决策树图,crtree_ui.R
 Generating predictions,正在生成预测,"crtree_ui.R, gbt_ui.R, logistic_ui.R,conjoint_ui.R"
 Generating prediction plot,正在生成预测图,"crtree_ui.R, gbt_ui.R, logistic_ui.R,conjoint_ui.R"
 Generating tree diagramm,正在生成树图,crtree_ui.R
-Model > Estimate,模型 > 估计,"crtree_ui.R, logistic_ui.R"
+Model > Estimate,模型方法 > 估计,"crtree_ui.R, logistic_ui.R"
 ** Press the Estimate button to estimate the model **,** 点击“估计模型”按钮来估计模型 **,"crtree_ui.R, gbt_ui.R,conjoint_ui.R"
 Please select one or more explanatory variables.,请选择一个或多个自变量。,"crtree_ui.R, gbt_ui.R, nn_ui.R"
 Max,最大化,dtree_ui.R
@@ -689,7 +689,7 @@ Select decisions to evaluate,选择要评估的决策,dtree_ui.R
           <i id='dtree_sense_del' title='Remove variable' href='#' class='action-button fa fa-minus-circle'></i></label>","<label>添加变量: <i id='dtree_sense_add' title='添加变量' href='#' class='action-button fa fa-plus-circle'></i>
           <i id='dtree_sense_del' title='删除变量' href='#' class='action-button fa fa-minus-circle'></i></label>",dtree_ui.R
 Step:,步长:,dtree_ui.R
-Model,模型,"dtree_ui.R,init.R"
+Model,模型方法,"dtree_ui.R,init.R"
 Decision analysis,决策分析,"dtree_ui.R,init.R"
 <i title='Report results' class='fa fa-edit action-button' href='#dtree_report1' id='dtree_report1'></i>,<i title='报告结果' class='fa fa-edit action-button' href='#dtree_report1' id='dtree_report1'></i>,dtree_ui.R
 <i title='Report results & Screenshot' class='fa fa-camera action-button aligncenter' href='#dtree_screenshot1' id='dtree_screenshot1' onclick='generate_screenshot();'></i>,<i title='报告结果并截图' class='fa fa-camera action-button aligncenter' href='#dtree_screenshot1' id='dtree_screenshot1' onclick='generate_screenshot();'></i>,dtree_ui.R
@@ -757,7 +757,7 @@ Save model evaluation plot,保存模型评估图,"evalbin_ui.R, evalreg_ui.R"
 Save confusion plots,保存混淆图,evalbin_ui.R
 Save uplift plots,保存提升图,evalbin_ui.R
 Evaluate,评估,"evalbin_ui.R,init.R"
-Model > Evaluate,模型 > 评估,"evalbin_ui.R, evalreg_ui.R"
+Model > Evaluate,模型方法 > 评估,"evalbin_ui.R, evalreg_ui.R"
 ** Press the Evaluate button to evaluate models **,** 请点击“评估”按钮以评估模型 **,"evalbin_ui.R, evalreg_ui.R"
 <label>More than 50 levels. Please choose another response variable</label>,<label>超过 50 个水平。请选择其他响应变量</label>,evalbin_ui.R
 "This analysis requires a response variable of type factor and one or more
@@ -784,7 +784,7 @@ Sub-sample:,子样本比例：,gbt_ui.R
 # rounds:,迭代轮数：,gbt_ui.R
 Early stopping:,提前停止：,gbt_ui.R
 Gradient Boosted Trees,梯度提升树,"gbt_ui.R,init.R"
-Model > Trees,模型 > 树模型,gbt_ui.R
+Model > Trees,模型方法 > 树模型,gbt_ui.R
 ** Select prediction input **,** 请选择预测输入 **,"gbt_ui.R, logistic_ui.R,conjoint_ui.R"
 ** Select data for prediction **,** 请选择用于预测的数据 **,"gbt_ui.R, logistic_ui.R,conjoint_ui.R"
 ** Enter prediction commands **,** 请输入预测命令 **,"gbt_ui.R, logistic_ui.R,conjoint_ui.R"
@@ -796,7 +796,7 @@ Save gradient boosted trees prediction plot,保存梯度提升树预测图,gbt_u
 Save gradient boosted trees plot,保存梯度提升树图,gbt_ui.R
 This analysis requires a response variable with two levels and one\nor more explanatory variables. If these variables are not available\nplease select another dataset.\n\n,此分析需要一个具有两个水平的响应变量和一个\n或多个解释变量。如果这些变量不可用\n请选择其他数据集。\n\n,gbt_ui.R
 This analysis requires a response variable of type integer\nor numeric and one or more explanatory variables.\nIf these variables are not available please select another dataset.\n\n,此分析需要一个整数类型的响应变量\n或数值型，以及一个或多个解释变量。\n如果这些变量不可用，请选择其他数据集。\n\n,gbt_ui.R
-Predict,预测,"gbt_ui.R,conjoint_ui.R"
+Predict,预测,"gbt_ui.R,conjoint_ui.R,crtree_ui.R"
 Storing residuals,存储残差,logistic_ui.R
 Save coefficients,保存系数,logistic_ui.R
 Save logistic prediction plot,保存逻辑回归预测图,logistic_ui.R
@@ -1090,7 +1090,7 @@ Radiant docs,Radiant文档,global.R
 Report issue,报告问题,global.R
 Design,设计,init.R
 Sample,样本,init.R
-Basics,基础,init.R
+Basics,基础统计,init.R
 Probability,概率,init.R
 Means,均值,init.R
 Proportions,比例,init.R
@@ -1127,12 +1127,12 @@ Base dir:,根目录：,global.R
 Generate descriptive statistics with one click,一键生成描述性统计,"quickgen_basic_ui.R,init.R"
 Oneclick generation > Generate descriptive statistics,一键生成 > 生成描述性统计,quickgen_basic_ui.R
 Oneclick generation,一键生成,init.R
-LLM generates descriptive statistics,大模型生成描述性统计,init.R
+AI generates descriptive statistics,大模型生成描述性统计,"init.R,quickgen_ai_ui.R"
 Select All,全选,quickgen_basic_ui.R
 Deselect All,全不选,quickgen_basic_ui.R
 Invert,反选,quickgen_basic_ui.R
 Radiant screenshot,截图,radiant.R
-Cancel,取消,radiant.R
+Cancel,取消,"radiant.R,quickgen_ai_ui.R"
 Table,表格,quickgen_basic_ui.R
 OneClick table generation,一键成表,quickgen_basic_ui.R
 Select numeric variables,选择数值变量,quickgen_basic_ui.R
@@ -1143,3 +1143,46 @@ Select X variable(s),选择X变量,quickgen_basic_ui.R
 No data available,暂无数据,quickgen_basic_ui.R
 No numerical variable available,无可用数值变量,quickgen_basic_ui.R
 ### Current data overview,### 当前数据概况,quickgen_basic_ui.R
+Describe your analysis request:,描述您的分析请求：,quickgen_ai_ui.R
+Oneclick generation > AI generates descriptive statistics,一键生成 > 大模型生成描述性统计,quickgen_ai_ui.R
+AI assistant,AI助手,quickgen_ai_ui.R
+Run code,运行,quickgen_ai_ui.R
+Edit code,编辑,quickgen_ai_ui.R
+Generated R code,生成的R代码,quickgen_ai_ui.R
+Send,发送,quickgen_ai_ui.R
+e. g. Please help me draw a scatter plot of diamonds prices and carats,e.g. 请帮我画一张 diamonds 价格与克拉的散点图,quickgen_ai_ui.R
+Please enter an analysis request,请输入分析请求,quickgen_ai_ui.R
+Save Changes,保存,quickgen_ai_ui.R
+Edit R Code,编辑R代码,quickgen_ai_ui.R
+Save AI-generated plot,保存大模型生成的图表,quickgen_ai_ui.R
+Edit the generated R code here...,在此处编辑生成的R代码...,quickgen_ai_ui.R
+Normality test,正态性检验,init.R
+Homogeneity of variance test,方差齐性检验,init.R
+Basics > Normality,基础统计 > 正态性,normality_test_ui.R
+Shapiro-Wilk,SW 检验,normality_test_ui.R
+Kolmogorov-Smirnov,K-S 检验,normality_test_ui.R
+Anderson-Darling,AD 检验,normality_test_ui.R
+Basics > Homogeneity,基础统计 > 方差齐性,homo_variance_test_ui.R
+Grouping variable:,分组变量：,homo_variance_test_ui.R
+Test method:,检验方法：,homo_variance_test_ui.R
+Levene,莱文检验,homo_variance_test_ui.R
+Bartlett,巴特利特检验,homo_variance_test_ui.R
+Fligner,弗林格检验,homo_variance_test_ui.R
+Cox Proportional Hazards Regression,比例风险回归,init.R
+Support Vector Machine (SVM),支持向量机（SVM）,init.R
+Kernel:,核函数：,svm_ui.R
+Linear,线性,svm_ui.R
+Polynomial,多项式,svm_ui.R
+Radial,径向基,svm_ui.R
+Cost (C):,惩罚系数 (C)：,svm_ui.R
+Gamma:,伽马系数：,svm_ui.R
+Coef0:,常数项：,svm_ui.R
+Epsilon (tube):,Epsilon 间隔带：,svm_ui.R
+Estimate class probabilities,估计类别概率,svm_ui.R
+Choose Excel file:,选择Excel文件：,manage_ui.R
+Sheet index (1-based):,工作表索引（从1开始）：,manage_ui.R
+First row as header,第一行为表头,manage_ui.R
+Time variable:,生存时间变量：,cox_ui.R
+Status variable:,事件状态变量：,cox_ui.R
+AI running...,大模型运行中...,quickgen_ai_ui.R
+Warning:Please enter a request related to descriptive statistics or visualization.,警告：请输入与描述性统计或可视化相关的请求。,quickgen_ai_ui.R
diff --git a/radiant.quickgen/DESCRIPTION b/radiant.quickgen/DESCRIPTION
index 9f58e63a931a8b8c7fa2c153e798f22812405802..425bf4ce2cb9c21c963b0408f794e6fae8993b6e 100644
--- a/radiant.quickgen/DESCRIPTION
+++ b/radiant.quickgen/DESCRIPTION
@@ -2,3 +2,21 @@ Package: radiant.quickgen
 Version: 0.0.1
 Title: Quick Generator table and chart for Radiant
 Description: Provides a simple data generator for the Radiant interface.
+Depends:
+    R (>= 4.3.0),
+    radiant.data (>= 1.6.6)
+Imports:
+    shiny (>= 1.8.1),
+    shiny.i18n,
+    httr2 (>= 1.0.0),
+    shinyjs,
+    shinyAce,
+    shinyWidgets(>= 0.8.0),
+    patchwork
+Suggests:
+    testthat (>= 2.0.0),
+    pkgdown (>= 1.1.0),
+    markdown (>= 1.3)
+Encoding: UTF-8
+Language: en-US
+RoxygenNote: 7.3.2
diff --git a/radiant.quickgen/NAMESPACE b/radiant.quickgen/NAMESPACE
new file mode 100644
index 0000000000000000000000000000000000000000..907d6115bd4764254075ad795afa118c89879532
--- /dev/null
+++ b/radiant.quickgen/NAMESPACE
@@ -0,0 +1,40 @@
+# Generated by roxygen2: do not edit by hand
+
+S3method(dtab,explore)
+S3method(store,explore)
+S3method(summary,explore)
+export(ai_generate)
+export(ai_get_data_call)
+export(ai_run_code)
+export(build_r_prompt)
+export(chat_completion)
+export(cv)
+export(does_vary)
+export(empty_level)
+export(explore)
+export(flip)
+export(ln)
+export(me)
+export(meprop)
+export(modal)
+export(n_missing)
+export(n_obs)
+export(p01)
+export(p025)
+export(p05)
+export(p10)
+export(p25)
+export(p75)
+export(p90)
+export(p95)
+export(p975)
+export(p99)
+export(prop)
+export(qscatter)
+export(sdpop)
+export(sdprop)
+export(se)
+export(seprop)
+export(varpop)
+export(varprop)
+export(visualize)
diff --git a/radiant.quickgen/R/quickgen_ai.R b/radiant.quickgen/R/quickgen_ai.R
index 696fd7d684532af846334f854e1770ef2113292c..7107e9aec41ed4b30f7292b5af735ce6bed82cfa 100644
--- a/radiant.quickgen/R/quickgen_ai.R
+++ b/radiant.quickgen/R/quickgen_ai.R
@@ -1,9 +1,98 @@
-#' 一键生成模块服务器逻辑
+# === 配置 ===
+MODELSCOPE_OPENAI_URL <- "https://api-inference.modelscope.cn/v1"
+MODELSCOPE_API_KEY    <- Sys.getenv("MODELSCOPE_API_KEY", "ms-b2746d72-f897-4faf-8089-89e5e511ed5a")
+MODEL_ID              <- "deepseek-ai/DeepSeek-V3.1"
+
+# === 低层封装：单次对话 ===
 #' @export
-quickgen_server <- function(input, output, session, r_data, r_info, r_state) {
-  # 为模块创建命名空间
-  ns <- session$ns
+chat_completion <- function(user_prompt,
+                            max_tokens = 1500,
+                            temperature = 0.3) {
+  req <- httr2::request(paste0(MODELSCOPE_OPENAI_URL, "/chat/completions")) %>%
+    httr2::req_headers(
+      "Authorization" = paste("Bearer", MODELSCOPE_API_KEY),
+      "Content-Type"  = "application/json"
+    ) %>%
+    httr2::req_body_json(list(
+      model       = MODEL_ID,
+      messages    = list(list(role = "user", content = user_prompt)),
+      temperature = temperature,
+      max_tokens  = max_tokens,
+      stream      = FALSE
+    ))
   
-  # 空函数，确保模块能正确加载
-  # 后续开发时可在此添加实际逻辑
+  resp <- httr2::req_perform(req)
+  body <- httr2::resp_body_json(resp)
+  
+  if (is.null(body$choices[[1]]$message$content))
+    stop("ModelScope API 返回空内容：", body)
+  
+  body$choices[[1]]$message$content
+}
+
+# === 构造发给模型的 Prompt ===
+#' @export
+build_r_prompt <- function(user_prompt, data_call) {
+  sprintf(
+    "你是 R 语言专家，必须严格遵守以下规则：
+
+〓 输出格式 〓
+- 只返回可运行 R 代码，用 ```r 包裹，禁止任何解释、注释、空行。
+- 若用户请求不符合下方【白名单】，一律返回空代码块（仅 ```r\n``` ），不对话。
+
+〓 白名单关键词（必须至少出现 1 个）〓
+箱线图|柱状图|条形图|散点图|折线图|密度图|直方图|热图|森林图|瀑布图|饼图|气泡图|生存曲线|KM 曲线|ggsurvplot|tbl_summary|tableone|CreateTableOne|描述性统计|基线表|相关性|group comparison|distribution|ggplot|geom_|patchwork
+
+〓 否定示例（立即返回空块）〓
+- 仅输入：“图表”“表格”“画图”“来张图”
+- 非医学/统计描述：笑话、故事、计算、翻译、写文章、写代码注释、解释概念、生成非 ggplot 图形（base、lattice）
+
+〓 技术细节 〓
+1. 数据集已读入：%s
+2. 主题函数带括号：theme_minimal()、theme_bw() ...
+3. 多张图用 patchwork 拼页。
+4. 包函数写全名，不得省略括号。
+
+用户请求：%s",
+    data_call, user_prompt
+  )
+}
+
+#' @export
+ai_generate <- function(prompt, dataset, envir = parent.frame()) {
+  data_call <- ai_get_data_call(dataset, envir)
+  sys_prompt <- build_r_prompt(prompt, data_call)
+  r_code     <- try(chat_completion(sys_prompt), silent = TRUE)
+  if (inherits(r_code, "try-error"))
+    stop("AI API error: ", attr(r_code, "condition")$message)
+  
+  r_code <- gsub("(?s)```r\\s*|```", "", r_code, perl = TRUE)
+  r_code <- trimws(r_code)
+  
+  if (r_code == "") {
+    return(list(r_code = "", 
+                type    = "empty",
+                auto_run = FALSE))
+  }
+  
+  r_code <- gsub("(theme_minimal|theme_bw|theme_classic|theme_gray|theme_void|theme_dark)\\b(?!\\s*\\()",
+                 "\\1()", r_code, perl = TRUE)
+  r_code <- paste0(data_call, "\n", r_code)
+  
+  has_gg  <- grepl("ggplot\\(|geom_", r_code)
+  has_tbl <- grepl("data\\.frame\\(|tibble\\(|tbl_summary|tableOne|CreateTableOne", r_code)
+  type    <- if (has_gg) "plot" else if (has_tbl) "table" else "text"
+  list(r_code = r_code, type = type, auto_run = TRUE)
+}
+
+#' @export
+ai_get_data_call <- function(dataset, envir) {
+  df_name <- if (is_string(dataset)) dataset else deparse1(substitute(dataset))
+  paste0("df <- eval(quote(get_data(\"", df_name, "\", envir = ",
+         deparse1(substitute(envir)), ")), envir = parent.frame())")
+}
+
+#' @export
+ai_run_code <- function(r_code, envir = parent.frame()) {
+  eval(parse(text = r_code), envir = envir)
 }
\ No newline at end of file
diff --git a/radiant.quickgen/R/quickgen_basic.R b/radiant.quickgen/R/quickgen_basic.R
index 02da8b09f2838cdf53538c41bf7bca7eccdf6f1c..da304f79797ebfc7a2ae11781b59bd9124df562a 100644
--- a/radiant.quickgen/R/quickgen_basic.R
+++ b/radiant.quickgen/R/quickgen_basic.R
@@ -1,4 +1,4 @@
-
+#' @export
 explore <- function(dataset, vars = "", byvar = "", fun = c("mean", "sd"),
                     top = "fun", tabfilt = "", tabsort = "", tabslice = "",
                     nr = Inf, data_filter = "", arr = "", rows = NULL,
@@ -171,7 +171,7 @@ explore <- function(dataset, vars = "", byvar = "", fun = c("mean", "sd"),
   ) %>% add_class("explore")
 }
 
-
+#' @export
 summary.explore <- function(object, dec = 3, ...) {
   cat("Explore\n")
   cat("Data        :", object$df_name, "\n")
@@ -209,7 +209,7 @@ summary.explore <- function(object, dec = 3, ...) {
   invisible()
 }
 
-
+#' @export
 store.explore <- function(dataset, object, name, ...) {
   if (missing(name)) {
     object$tab
@@ -225,7 +225,7 @@ store.explore <- function(dataset, object, name, ...) {
   }
 }
 
-
+#' @export
 flip <- function(expl, top = "fun") {
   cvars <- expl$byvar %>%
     (function(x) if (is.empty(x[1])) character(0) else x)
@@ -245,7 +245,7 @@ flip <- function(expl, top = "fun") {
   expl$tab
 }
 
-
+#' @export
 dtab.explore <- function(object, dec = 3, searchCols = NULL,
                          order = NULL, pageLength = NULL,
                          caption = NULL, ...) {
@@ -330,31 +330,31 @@ dtab.explore <- function(object, dec = 3, searchCols = NULL,
 ## turn functions below into functional ...
 ###########################################
 
-
+#' @export
 n_obs <- function(x, ...) length(x)
-
+#' @export
 n_missing <- function(x, ...) sum(is.na(x))
-
+#' @export
 p01 <- function(x, na.rm = TRUE) quantile(x, .01, na.rm = na.rm)
-
+#' @export
 p025 <- function(x, na.rm = TRUE) quantile(x, .025, na.rm = na.rm)
-
+#' @export
 p05 <- function(x, na.rm = TRUE) quantile(x, .05, na.rm = na.rm)
-
+#' @export
 p10 <- function(x, na.rm = TRUE) quantile(x, .1, na.rm = na.rm)
-
+#' @export
 p25 <- function(x, na.rm = TRUE) quantile(x, .25, na.rm = na.rm)
-
+#' @export
 p75 <- function(x, na.rm = TRUE) quantile(x, .75, na.rm = na.rm)
-
+#' @export
 p90 <- function(x, na.rm = TRUE) quantile(x, .90, na.rm = na.rm)
-
+#' @export
 p95 <- function(x, na.rm = TRUE) quantile(x, .95, na.rm = na.rm)
-
+#' @export
 p975 <- function(x, na.rm = TRUE) quantile(x, .975, na.rm = na.rm)
-
+#' @export
 p99 <- function(x, na.rm = TRUE) quantile(x, .99, na.rm = na.rm)
-
+#' @export
 cv <- function(x, na.rm = TRUE) {
   m <- mean(x, na.rm = na.rm)
   if (m == 0) {
@@ -364,17 +364,17 @@ cv <- function(x, na.rm = TRUE) {
     sd(x, na.rm = na.rm) / m
   }
 }
-
+#' @export
 se <- function(x, na.rm = TRUE) {
   if (na.rm) x <- na.omit(x)
   sd(x) / sqrt(length(x))
 }
-
+#' @export
 me <- function(x, conf_lev = 0.95, na.rm = TRUE) {
   if (na.rm) x <- na.omit(x)
   se(x) * qt(conf_lev / 2 + .5, length(x) - 1, lower.tail = TRUE)
 }
-
+#' @export
 prop <- function(x, na.rm = TRUE) {
   if (na.rm) x <- na.omit(x)
   if (is.numeric(x)) {
@@ -387,36 +387,36 @@ prop <- function(x, na.rm = TRUE) {
     NA
   }
 }
-
+#' @export
 varprop <- function(x, na.rm = TRUE) {
   p <- prop(x, na.rm = na.rm)
   p * (1 - p)
 }
-
+#' @export
 sdprop <- function(x, na.rm = TRUE) sqrt(varprop(x, na.rm = na.rm))
-
+#' @export
 seprop <- function(x, na.rm = TRUE) {
   if (na.rm) x <- na.omit(x)
   sqrt(varprop(x, na.rm = FALSE) / length(x))
 }
-
+#' @export
 meprop <- function(x, conf_lev = 0.95, na.rm = TRUE) {
   if (na.rm) x <- na.omit(x)
   seprop(x) * qnorm(conf_lev / 2 + .5, lower.tail = TRUE)
 }
-
+#' @export
 varpop <- function(x, na.rm = TRUE) {
   if (na.rm) x <- na.omit(x)
   n <- length(x)
   var(x) * ((n - 1) / n)
 }
-
+#' @export
 sdpop <- function(x, na.rm = TRUE) sqrt(varpop(x, na.rm = na.rm))
-
+#' @export
 ln <- function(x, na.rm = TRUE) {
   if (na.rm) log(na.omit(x)) else log(x)
 }
-
+#' @export
 does_vary <- function(x, na.rm = TRUE) {
   ## based on http://stackoverflow.com/questions/4752275/test-for-equality-among-all-elements-of-a-single-vector
   if (length(x) == 1L) {
@@ -429,7 +429,7 @@ does_vary <- function(x, na.rm = TRUE) {
     }
   }
 }
-
+#' @export
 empty_level <- function(x) {
   if (!is.factor(x)) x <- as.factor(x)
   levs <- levels(x)
@@ -443,7 +443,7 @@ empty_level <- function(x) {
   }
   x
 }
-
+#' @export
 modal <- function(x, na.rm = TRUE) {
   if (na.rm) x <- na.omit(x)
   unv <- unique(x)
@@ -451,7 +451,7 @@ modal <- function(x, na.rm = TRUE) {
 }
 
 #—————————————————————————————————————————————————绘图部分———————————————————————————————————————————
-
+#' @export
 visualize <- function(dataset, xvar, yvar = "", comby = FALSE, combx = FALSE,
                       type = ifelse(is.empty(yvar), "dist", "scatter"), nrobs = -1,
                       facet_row = ".", facet_col = ".", color = "none", fill = "none",
@@ -1131,7 +1131,7 @@ visualize <- function(dataset, xvar, yvar = "", comby = FALSE, combx = FALSE,
       (function(x) if (isTRUE(shiny)) x else print(x))
   }
 }
-
+#' @export
 qscatter <- function(dataset, xvar, yvar, lev = "", fun = "mean", bins = 20) {
   if (is.character(dataset[[yvar]])) {
     dataset <- mutate_at(dataset, .vars = yvar, .funs = as.factor)
diff --git a/radiant.quickgen/inst/app/init.R b/radiant.quickgen/inst/app/init.R
index 403e99a81536a39860cb43289dc517a8c2dfe800..636bf72ef54a9fc557be505ccdc9496f15ec05dd 100644
--- a/radiant.quickgen/inst/app/init.R
+++ b/radiant.quickgen/inst/app/init.R
@@ -15,7 +15,7 @@ options(
           tags$script(src = "www_quickgen/js/run_return.js")
         ),
         tabPanel(i18n$t("Generate descriptive statistics with one click"), uiOutput("quickgen_basic")),
-        tabPanel(i18n$t("LLM generates descriptive statistics"), uiOutput("quickgen_ai"))
+        tabPanel(i18n$t("AI generates descriptive statistics"), uiOutput("quickgen_ai"))
       )
     )
 )
\ No newline at end of file
diff --git a/radiant.quickgen/inst/app/tools/analysis/quickgen_ai_ui.R b/radiant.quickgen/inst/app/tools/analysis/quickgen_ai_ui.R
index 86b2a99816efcd09cb1ebf14bb45ec8d6e643921..72d9270fe42e1b9c0eae0883f6f486d008353469 100644
--- a/radiant.quickgen/inst/app/tools/analysis/quickgen_ai_ui.R
+++ b/radiant.quickgen/inst/app/tools/analysis/quickgen_ai_ui.R
@@ -1,9 +1,295 @@
-#' 大模型生成描述性统计界面
-quickgen_ai_ui <- function() {
+# quickgen_ai_ui.R
+library(shinyjs)
+library(shinyAce)
+
+## ==================== 右下角浮框 ====================
+ui_ai_progress <- tags$div(
+  id = "ai_progress_box",
+  style = "display:none;
+           position:fixed;
+           bottom:15px; right:15px;
+           width:220px; z-index:9999;
+           background:#f5f5f5; color:#333;
+           border:1px solid #337ab7; border-radius:4px;
+           padding:10px 15px; box-shadow:0 2px 8px rgba(0,0,0,.25);",
+  tags$strong(i18n$t("AI running...")),
+  tags$div(class = "progress",
+           tags$div(class = "progress-bar progress-bar-striped active",
+                    style = "width:100%"))
+)
+
+## ======== 警告弹窗========
+ui_ai_warn <- tags$div(
+  id = "ai_warn_box",
+  style = "display:none;
+           position:fixed;
+           bottom:15px; right:15px;
+           width:220px; z-index:9999;
+           background:#fff3cd; color:#856404;
+           border:1px solid #ffeaa7; border-radius:4px;
+           padding:10px 15px; box-shadow:0 2px 8px rgba(0,0,0,.25);",
+  tags$strong(i18n$t("Warning:Please enter a request related to descriptive statistics or visualization."))
+)
+
+## ==================== 统一入口 ====================
+output$quickgen_ai <- renderUI({
+  stat_tab_panel(
+    menu      = i18n$t("Oneclick generation > AI generates descriptive statistics"),
+    tool      = i18n$t("AI generates descriptive statistics"),
+    tool_ui   = "ai_main_ui",
+    output_panels = tabPanel(
+      title = i18n$t("AI assistant"),
+      value = "ai_panel",
+      uiOutput("ai_result_area")
+    )
+  )
+})
+
+## ==================== 右侧 AI 面板 ====================
+output$ai_main_ui <- renderUI({
   tagList(
-    h3("大模型生成描述性统计"),
-    p("正在开发中...")
+    useShinyjs(),
+    ui_ai_progress,
+    ui_ai_warn,
+    wellPanel(
+      i18n$t("Describe your analysis request"),
+      returnTextAreaInput("ai_prompt",
+                          label   = NULL,
+                          placeholder = i18n$t("e. g. Please help me draw a scatter plot of diamonds prices and carats"),
+                          rows    = 4,
+                          value   = state_init("ai_prompt", "")),
+      fluidRow(
+        column(6, uiOutput("ui_ai_submit")),
+        column(6, uiOutput("ai_loading"))
+      )
+    ),
+    
+    wellPanel(
+      i18n$t("Generated R code"),
+      uiOutput("ai_r_code_block"),
+      fluidRow(
+        column(6, actionButton("ai_run_code", i18n$t("Run code"), icon = icon("play"), class = "btn-success")),
+        column(6, actionButton("ai_edit_code", i18n$t("Edit code"), icon = icon("edit"), class = "btn-default"))
+      )
+    ),
+    
+    help_and_report(
+      modal_title = i18n$t("AI generates descriptive statistics"),
+      fun_name    = "quickgen_ai",
+      help_file   = inclMD(file.path(getOption("radiant.path.quickgen"), "app/tools/help/quickgen_ai.md")),
+      lic = "by-sa"
+    )
   )
+})
+
+## ==================== 控件渲染 ====================
+output$ui_ai_submit <- renderUI({
+  req(input$dataset)
+  actionButton("ai_submit", i18n$t("Send"), icon = icon("magic"), class = "btn-primary")
+})
+
+output$ai_loading <- renderUI({
+  if (isTRUE(r_values$ai_loading))
+    tags$div(class = "progress",
+             tags$div(class = "progress-bar progress-bar-striped active",
+                      style = "width:100%",
+                      i18n$t("Calling AI model...")))
+})
+
+## ==================== reactiveValues ====================
+r_values <- reactiveValues(
+  ai_r_code      = "",
+  ai_result_type = "text",
+  ai_result_ready = FALSE,
+  ai_loading     = FALSE
+)
+
+## ==================== 生成代码 ====================
+observeEvent(input$ai_submit, {
+  if (is.empty(input$ai_prompt))
+    return(showNotification(i18n$t("Please enter an analysis request"), type = "error"))
+  
+  r_values$ai_loading <- TRUE
+  shinyjs::show("ai_progress_box")          # 显示右下角进度框
+  on.exit({
+    r_values$ai_loading <- FALSE
+    shinyjs::hide("ai_progress_box")        # 无论成功失败都隐藏
+  })
+  
+  res <- try(do.call(ai_generate,
+                     list(prompt  = input$ai_prompt,
+                          dataset = input$dataset,
+                          envir   = r_data)),
+             silent = TRUE)
+  if (inherits(res, "try-error")) {
+    showNotification(paste(i18n$t("AI API error:"), res), type = "error")
+    return()
+  }
+  
+  r_values$ai_r_code      <- res$r_code
+  r_values$ai_result_type <- res$type
+  r_values$ai_result_ready <- FALSE
+  r_values$auto_run       <- res$auto_run
+  
+  if (res$type == "empty") {
+    shinyjs::show("ai_warn_box")
+    shinyjs::delay(3000, shinyjs::hide("ai_warn_box"))
+    return()
+  }
+  
+  if (isTRUE(r_values$auto_run))
+    shinyjs::click("ai_run_code")
+})
+
+## ==================== 显示 R 代码 ====================
+output$ai_r_code_block <- renderUI({
+  codes <- r_values$ai_r_code
+  tags$pre(codes, style = "background:#f5f5f5; padding:10px; border-radius:4px;
+                           font-family:monospace; white-space:pre-wrap; min-height:100px;")
+})
+
+## ==================== 运行代码 ====================
+observeEvent(input$ai_run_code, {
+  shinyjs::hide("ai_progress_box")   
+  if (is.empty(r_values$ai_r_code)) return()
+  
+  if (trimws(r_values$ai_r_code) == "" || identical(r_values$ai_result_type, "empty")) {
+    shinyjs::show("ai_warn_box")
+    shinyjs::delay(3000, shinyjs::hide("ai_warn_box"))
+    return()
+  }
+  
+  tryCatch({
+    result <- do.call(ai_run_code,
+                      list(r_code = r_values$ai_r_code, envir = r_data))
+    r_data$ai_temp_result <- result
+    
+    if (inherits(result, "gg") || inherits(result, "ggplot")) {
+      r_values$ai_result_type <- "plot"
+      output$ai_result_plot <- renderPlot(print(result))
+    } else if (is.data.frame(result) || is.matrix(result)) {
+      r_values$ai_result_type <- "table"
+      output$ai_result_table <- DT::renderDataTable(
+        DT::datatable(result, options = list(scrollX = TRUE, pageLength = 10)))
+    } else {
+      r_values$ai_result_type <- "text"
+      output$ai_result_text <- renderText(capture.output(print(result)))
+    }
+    r_values$ai_result_ready <- TRUE
+  }, error = function(e) {
+    r_values$ai_result_type <- "error"
+    output$ai_result_error <- renderText(paste0(i18n$t("Error: "), e$message))
+    r_values$ai_result_ready <- TRUE
+    showNotification(paste0(i18n$t("Run code error: "), e$message),
+                     type = "error", duration = NULL)
+  })
+}, ignoreInit = TRUE)
+
+## ======== 结果展示区========
+output$ai_result_area <- renderUI({
+  req(r_values$ai_result_ready)
+  tagList(
+    conditionalPanel(
+      condition = "output.ai_result_type == 'plot'",
+      download_link("dlp_ai_plot"), br(),            
+      plotOutput("ai_result_plot", width = "100%", height = "500px")
+    ),
+    conditionalPanel(
+      condition = "output.ai_result_type == 'table'",
+      download_link("dlp_ai_table"), br(),          
+      DT::dataTableOutput("ai_result_table")
+    ),
+    conditionalPanel(
+      condition = "output.ai_result_type == 'text' || output.ai_result_type == 'error'",
+      verbatimTextOutput("ai_result_text")
+    )
+  )
+})
+
+
+output$ai_result_type <- reactive({
+  r_values$ai_result_type 
+})
+
+outputOptions(output, "ai_result_type", suspendWhenHidden = FALSE)
+
+## ==================== 编辑代码模态框 ====================
+observeEvent(input$ai_edit_code, {
+  showModal(
+    modalDialog(
+      title = i18n$t("Edit R Code"),
+      size  = "l",
+      footer = tagList(
+        actionButton("ai_save_code", i18n$t("Save Changes"), class = "btn-primary"),
+        modalButton(i18n$t("Cancel"))
+      ),
+      aceEditor(
+        "ai_code_editor",
+        mode = "r",
+        theme = getOption("radiant.ace_theme", "tomorrow"),
+        wordWrap = TRUE,
+        value = r_values$ai_r_code,
+        placeholder = i18n$t("Edit the generated R code here..."),
+        vimKeyBinding = getOption("radiant.ace_vim.keys", FALSE),
+        tabSize = getOption("radiant.ace_tabSize", 2),
+        useSoftTabs = getOption("radiant.ace_useSoftTabs", TRUE),
+        showInvisibles = getOption("radiant.ace_showInvisibles", FALSE),
+        autoScrollEditorIntoView = TRUE,
+        minLines = 15,
+        maxLines = 30
+      )
+    )
+  )
+})
+
+## ==================== 保存代码 ====================
+observeEvent(input$ai_save_code, {
+  r_values$ai_r_code <- input$ai_code_editor
+  r_values$auto_run <- FALSE
+  removeModal()
+})
+
+## ==================== PNG 下载处理器 ====================
+dlp_ai_plot <- function(path) {
+  result <- r_data$ai_temp_result
+  if (inherits(result, "gg") || inherits(result, "ggplot")) {
+    png(path, width = 800, height = 500, res = 96)
+    print(result)
+    dev.off()
+  } else {
+    png(path, width = 400, height = 400)
+    plot(1, type = "n", axes = FALSE, xlab = "", ylab = "")
+    text(1, 1, "No plot available", cex = 1.5)
+    dev.off()
+  }
+}
+download_handler(
+  id = "dlp_ai_plot",
+  fun = dlp_ai_plot,
+  fn = function() paste0("plot_", Sys.Date()),
+  type = "png",
+  caption = i18n$t("Save AI-generated plot")
+)
+
+# ======== 表格 CSV 下载处理器 ========
+dlp_ai_table <- function(path) {
+  result <- r_data$ai_temp_result
+  if (is.data.frame(result)) {
+    write.csv(result, file = path, row.names = FALSE)
+  } else {
+    write.csv(data.frame(msg = "No table available"), file = path, row.names = FALSE)
+  }
 }
+download_handler(
+  id      = "dlp_ai_table",
+  fun     = dlp_ai_table,
+  fn      = function() paste0("table_", Sys.Date()),
+  type    = "csv",
+  caption = i18n$t("Save AI-generated table")
+)
 
-quickgen_ai_ui()
\ No newline at end of file
+## ==================== 报告 / 截图 ====================
+ai_report <- function() {}
+observeEvent(input$ai_report, ai_report())
+observeEvent(input$ai_screenshot, radiant_screenshot_modal("modal_ai_screenshot"))
+observeEvent(input$modal_ai_screenshot, { ai_report(); removeModal() })
\ No newline at end of file
diff --git a/radiant.quickgen/inst/app/tools/analysis/quickgen_basic_ui .txt b/radiant.quickgen/inst/app/tools/analysis/quickgen_basic_ui .txt
deleted file mode 100644
index 45407749489d93afb8c90588c23d461c56f86e1c..0000000000000000000000000000000000000000
--- a/radiant.quickgen/inst/app/tools/analysis/quickgen_basic_ui .txt	
+++ /dev/null
@@ -1,1115 +0,0 @@
-make_desc_text <- function(df) {
-  if (is.null(df) || nrow(df) == 0) return(i18n$t("No data available"))
-  ## 只保留数值列
-  num_cols <- sapply(df, is.numeric)
-  if (sum(num_cols) == 0) return("No numerical variable available")
-  df_num <- df[, num_cols, drop = FALSE]
-  
-  buf <- c(i18n$t("### Current data overview"))
-  buf <- c(buf, sprintf("- **Sample size**：%d records", nrow(df)))
-  ## 连续变量
-  for (v in names(df_num)) {
-    x <- df_num[[v]]
-    x <- x[!is.na(x)]
-    if (length(x) == 0) next
-    buf <- c(buf, sprintf(
-      "- **%s**: mean %.2f ± %.2f; median %.2f; range [%.2f, %.2f]; missing %.1f%%",
-      v,
-      mean(x), sd(x), median(x), min(x), max(x),
-      100 * (1 - length(x) / nrow(df))
-    ))
-  }
-  ## 分类变量
-  cat_cols <- sapply(df, function(z) is.factor(z) || is.character(z))
-  for (v in names(df)[cat_cols]) {
-    tbl <- table(df[[v]], useNA = "ifany")
-    lev_txt <- paste(sprintf("%s (%d, %.1f%%)",
-                             names(tbl), tbl,
-                             100 * tbl / sum(tbl)), collapse = "、")
-    buf <- c(buf, sprintf("- **%s**：%s", v, lev_txt))
-  }
-  paste(buf, collapse = "\n")
-}
-
-## quickgen_basic 的形参列表
-default_funs <- c("n_obs", "mean", "sd", "min", "max")
-qib_type <- c(
-  "分布图（dist）" = "dist", "密度图（density）" = "density", "散点图（scatter）" = "scatter",
-  "曲面图（surface）" = "surface", "折线图（line）" = "line", "条形图（bar）" = "bar", "箱线图（box）" = "box"
-)
-qib_check <- c(
-  "直线（line）" = "line", "局部加权回归（loess）" = "loess", 
-  "抖动（jitter）" = "jitter", 
-  "插值（interpolate）" = "interpolate"
-)
-qib_axes <- c(
-  "翻转坐标轴（flip）" = "flip", "X轴对数变换（log_x）" = "log_x", "Y轴对数变换（log_y）" = "log_y",
-  "Y轴缩放（scale_y）" = "scale_y", "密度（density）" = "density", "排序（sort）" = "sort"
-)
-qib_theme <- c(
-  "灰色主题（gray）" = "theme_gray", "黑白主题（bw）" = "theme_bw",
-  "明亮主题（light）" = "theme_light", "暗黑主题（dark）" = "theme_dark",
-  "极简主题（minimal）" = "theme_minimal", "经典主题（classic）" = "theme_classic"
-)
-
-os_type <- Sys.info()["sysname"]
-if (os_type == "Windows") {
-  fnt <- names(windowsFonts())
-  names(fnt) <- tools::toTitleCase(fnt)
-  qib_base_family <- c("Theme default" = "", fnt)
-} else {
-  qib_base_family <- c(
-    "Theme default" = "", "Helvetica" = "Helvetica", "Serif" = "serif",
-    "Sans" = "sans", "Mono" = "mono", "Courier" = "Courier", "Times" = "Times"
-  )
-}
-
-qib_labs <- c(i18n$t("title"), i18n$t("subtitle"), i18n$t("caption"), i18n$t("x"), i18n$t("y"))
-qib_add_labs <- function() {
-  lab_list <- list()
-  for (l in qib_labs) {
-    inp <- input[[paste0("qib_labs_", l)]]
-    if (!is.empty(inp)) lab_list[[l]] <- inp
-  }
-  lab_list
-}
-
-qgb_args <- as.list(formals(explore))
-qib_args <- as.list(formals(visualize))
-
-## 收集用户输入的 reactive 列表
-qgb_inputs <- reactive({
-  qgb_args$data_filter <- if (input$show_filter) input$data_filter else ""
-  qgb_args$arr         <- if (input$show_filter) input$data_arrange else ""
-  qgb_args$rows        <- if (input$show_filter) input$data_rows   else ""
-  qgb_args$dataset     <- input$dataset
-  
-  for (i in r_drop(names(qgb_args))) {
-    qgb_args[[i]] <- input[[paste0("qgb_", i)]]
-  }
-  qgb_args
-})
-
-qgb_sum_args <- as.list(if (exists("summary.explore")) {
-  formals(summary.explore)
-} else {
-  formals(radiant.data:::summary.explore)
-})
-
-qib_inputs <- reactive({
-  qib_args$data_filter <- if (isTRUE(input$show_filter)) input$data_filter else ""
-  qib_args$arr <- if (isTRUE(input$show_filter)) input$data_arrange else ""
-  qib_args$rows <- if (isTRUE(input$show_filter)) input$data_rows else ""
-  qib_args$dataset <- input$dataset
-  qib_args$shiny <- input$shiny
-  qib_args$labs <- qib_add_labs()
-  for (i in r_drop(names(qib_args), drop = c(i18n$t("dataset"), i18n$t("data_filter"), i18n$t("arr"), i18n$t("rows"), i18n$t("labs")))) {
-    qib_args[[i]] <- input[[paste0("qib_", i)]]
-  }
-  qib_args
-})
-
-## list of function inputs selected by user
-qgb_sum_inputs <- reactive({
-  ## loop needed because reactive values don't allow single bracket indexing
-  for (i in names(qgb_sum_args)) {
-    qgb_sum_args[[i]] <- input[[paste0("qgb_", i)]]
-  }
-  qgb_sum_args
-})
-
-## UI-elements
-output$ui_qgb_vars <- renderUI({
-  vars <- varnames()
-  req(available(vars))
-  selectizeInput(
-    "qgb_vars",
-    label = i18n$t("Numeric variable(s):"),
-    choices = vars,
-    selected = state_multiple("qgb_vars", vars, isolate(input$qgb_vars)),
-    multiple = TRUE,
-    options = list(
-      placeholder = i18n$t("Select numeric variables"),
-      plugins = list("remove_button", "drag_drop")
-    )
-  )
-})
-
-output$ui_qgb_byvar <- renderUI({
-  withProgress(message = i18n$t("Acquiring variable information"), value = 1, {
-    vars <- groupable_vars()
-  })
-  req(available(vars))
-  
-  if (any(vars %in% input$qgb_vars)) {
-    vars <- base::setdiff(vars, input$qgb_vars)
-    names(vars) <- varnames() %>%
-      (function(x) x[match(vars, x)]) %>%
-      names()
-  }
-  isolate({
-    ## if nothing is selected expl_byvar is also null
-    if ("qgb_byvar" %in% names(input) && is.null(input$qgb_byvar)) {
-      r_state$qgb_byvar <<- NULL
-    } else {
-      if (available(r_state$qgb_byvar) && all(r_state$qgb_byvar %in% vars)) {
-        vars <- unique(c(r_state$qgb_byvar, vars))
-        names(vars) <- varnames() %>%
-          (function(x) x[match(vars, x)]) %>%
-          names()
-      }
-    }
-  })
-  selectizeInput(
-    "qgb_byvar",
-    label = i18n$t("Group by:"), choices = vars,
-    selected = state_multiple("qgb_byvar", vars, isolate(input$qgb_byvar)),
-    multiple = TRUE,
-    options = list(
-      placeholder = i18n$t("Select group-by variable"),
-      plugins = list("remove_button", "drag_drop")
-    )
-  )
-})
-
-output$ui_qgb_fun <- renderUI({
-  r_funs <- getOption("radiant.functions") 
-  selected <- isolate(
-    if (is.empty(input$qgb_fun)) default_funs else input$qgb_fun
-  )
-  tagList(
-    div(
-      style = "margin-top: 5px; display: flex; gap: 3px; flex-wrap: wrap;",
-      actionButton("qgb_select_all", i18n$t("Select All"), 
-                   class = "btn-xs btn-primary", icon = icon("check-square")),
-      actionButton("qgb_deselect_all", i18n$t("Deselect All"), 
-                   class = "btn-xs btn-primary", icon = icon("square")),
-      actionButton("qgb_invert_selection", i18n$t("Invert"), 
-                   class = "btn-xs btn-primary", icon = icon("undo"))
-    ),
-    checkboxGroupInput(
-      inputId = "qgb_fun",
-      label   = i18n$t("Apply function(s):"),
-      choices = r_funs,
-      selected = selected
-    )
-  )
-})
-
-output$ui_qgb_top <- renderUI({
-  if (is.empty(input$qgb_vars)) {
-    return()
-  }
-  top_var <- setNames(
-    c("fun", "var", "byvar"),
-    c(i18n$t("Function"), i18n$t("Variables"), i18n$t("Group by"))
-  )
-  if (is.empty(input$qgb_byvar)) top_var <- top_var[1:2]
-  selectizeInput(
-    "qgb_top",
-    label = i18n$t("Column header:"),
-    choices = top_var,
-    selected = state_single("qgb_top", top_var, isolate(input$qgb_top)),
-    multiple = FALSE
-  )
-})
-
-output$ui_qgb_name <- renderUI({
-  req(input$dataset)
-  textInput("qgb_name", i18n$t("Store as:"), "", placeholder = i18n$t("Provide a table name"))
-})
-
-output$ui_qgb_run <- renderUI({
-  ## updates when dataset changes
-  req(input$dataset)
-  actionButton("qgb_run", i18n$t("OneClick table generation"), width = "100%", icon = icon("play", verify_fa = FALSE), class = "btn-success")
-})
-
-## add a spinning refresh icon if the table needs to be (re)calculated
-run_refresh(qgb_args, "qgb", init = "vars", label = i18n$t("OneClick table generation"), relabel = i18n$t("Update table"))
-
-#######################################
-# Visualize data
-#######################################
-output$ui_qib_type <- renderUI({
-  selectInput(
-    inputId = "qib_type", label = i18n$t("Plot-type:"), choices = qib_type,
-    selected = state_single("qib_type", qib_type),
-    multiple = FALSE
-  )
-})
-
-output$ui_qib_nrobs <- renderUI({
-  req(input$qib_type == "scatter")
-  nrobs <- nrow(.get_data())
-  choices <- c("1,000" = 1000, "5,000" = 5000, "10,000" = 10000, "All" = -1) %>%
-    .[. < nrobs]
-  selectInput(
-    "qib_nrobs", i18n$t("Number of data points plotted:"),
-    choices = choices,
-    selected = state_single("qib_nrobs", choices, 1000)
-  )
-})
-
-## Y - variable
-output$ui_qib_yvar <- renderUI({
-  req(input$qib_type)
-  vars <- varying_vars()
-  req(available(vars))
-  vars <- vars["date" != .get_class()[vars]]
-  if (input$qib_type %in% c("line", "bar", "scatter", "surface", "box")) {
-    vars <- vars["character" != .get_class()[vars]]
-  }
-  if (input$qib_type %in% c("box", "scatter")) {
-    vars <- vars["factor" != .get_class()[vars]]
-  }
-  
-  selectizeInput(
-    inputId = "qib_yvar",
-    label   = i18n$t("Y-variable:"),
-    choices = vars,
-    selected = state_multiple("qib_yvar", vars, isolate(input$qib_yvar)),
-    multiple = TRUE,
-    options = list(
-      placeholder = i18n$t("Select Y variable(s)"),
-      plugins     = list("remove_button", "drag_drop")
-    )
-  )
-})
-
-## X - variable
-output$ui_qib_xvar <- renderUI({
-  req(input$qib_type)
-  vars <- varying_vars()
-  req(available(vars))
-  if (input$qib_type == "dist")  vars <- vars["date"  != .get_class()[vars]]
-  if (input$qib_type == "density") vars <- vars["factor" != .get_class()[vars]]
-  if (input$qib_type %in% c("box", "bar")) vars <- groupable_vars_nonum()
-  
-  selectizeInput(
-    inputId = "qib_xvar",
-    label   = i18n$t("X-variable:"),
-    choices = vars,
-    selected = state_multiple("qib_xvar", vars, isolate(input$qib_xvar)),
-    multiple = TRUE,
-    options = list(
-      placeholder = i18n$t("Select X variable(s)"),
-      plugins     = list("remove_button", "drag_drop")
-    )
-  )
-})
-
-output$ui_qib_comby <- renderUI({
-  checkboxInput(
-    "qib_comby", i18n$t("Combine Y-variables in one plot"),
-    state_init("qib_comby", FALSE)
-  )
-})
-
-output$ui_qib_combx <- renderUI({
-  checkboxInput(
-    "qib_combx", i18n$t("Combine X-variables in one plot"),
-    state_init("qib_combx", FALSE)
-  )
-})
-
-observeEvent(length(input$qib_xvar) < 2, {
-  updateCheckboxInput(session, "qib_combx", value = FALSE)
-})
-
-observeEvent(length(input$qib_yvar) < 2, {
-  updateCheckboxInput(session, "qib_comby", value = FALSE)
-})
-
-observeEvent(input$qib_type, {
-  if (input$qib_type %in% c("dist", "density")) {
-    updateCheckboxInput(session, "qib_comby", value = FALSE)
-  } else {
-    updateCheckboxInput(session, "qib_combx", value = FALSE)
-  }
-})
-
-observeEvent(input$qib_check, {
-  if (!"loess" %in% input$qib_check && input$qib_smooth != 1) {
-    updateSliderInput(session, "qib_smooth", value = 1)
-  }
-})
-
-# output$ui_qib_facet_row <- renderUI({
-#   vars <- c("None" = ".", groupable_vars_nonum())
-#   selectizeInput(
-#     "qib_facet_row", i18n$t("Facet row:"), vars,
-#     selected = state_single("qib_facet_row", vars, init = "."),
-#     multiple = FALSE
-#   )
-# })
-
-# output$ui_qib_facet_col <- renderUI({
-#   vars <- c("None" = ".", groupable_vars_nonum())
-#   selectizeInput(
-#     "qib_facet_col", i18n$t("Facet column:"), vars,
-#     selected = state_single("qib_facet_col", vars, init = "."),
-#     multiple = FALSE
-#   )
-# })
-
-# output$ui_qib_color <- renderUI({
-#   req(input$qib_type)
-#   if (input$qib_type == "line") {
-#     vars <- c("None" = "none", groupable_vars())
-#   } else {
-#     vars <- c("None" = "none", varnames())
-#   }
-#   
-#   if (isTRUE(input$qib_comby) && length(input$qib_yvar) > 1) vars <- c("None" = "none")
-#   selectizeInput(
-#     "qib_color", i18n$t("Color:"), vars,
-#     multiple = FALSE,
-#     selected = state_single("qib_color", vars, init = "none")
-#   )
-# })
-
-# output$ui_qib_fill <- renderUI({
-#   vars <- c("None" = "none", groupable_vars())
-#   if (isTRUE(input$qib_combx) && length(input$qib_xvar) > 1) vars <- vars[1]
-#   selectizeInput(
-#     "qib_fill", i18n$t("Fill:"), vars,
-#     multiple = FALSE,
-#     selected = state_single("qib_fill", vars, init = "none")
-#   )
-# })
-
-# output$ui_qib_size <- renderUI({
-#   req(input$qib_type)
-#   isNum <- .get_class() %in% c("integer", "numeric", "ts")
-#   vars <- c("None" = "none", varnames()[isNum])
-#   if (isTRUE(input$qib_comby) && length(input$qib_yvar) > 1) vars <- c("None" = "none")
-#   selectizeInput(
-#     "qib_size", i18n$t("Size:"), vars,
-#     multiple = FALSE,
-#     selected = state_single("qib_size", vars, init = "none")
-#   )
-# })
-
-output$ui_qib_axes <- renderUI({
-  req(input$qib_type)
-  ind <- 1
-  if (input$qib_type %in% c("line", "scatter", "surface")) {
-    ind <- 1:3
-  } else if (input$qib_type == "dist") {
-    ind <- c(1:2, 5)
-  } else if (input$qib_type == "density") {
-    ind <- 1:2
-  } else if (input$qib_type %in% c("bar", "box")) {
-    ind <- c(1, 3)
-  }
-  if (!is.empty(input$qib_facet_row, ".") || !is.empty(input$qib_facet_col, ".")) ind <- c(ind, 4)
-  if (input$qib_type == "bar") ind <- c(ind, 6)
-  
-  checkboxGroupInput(
-    "qib_axes", NULL, qib_axes[ind],
-    selected = state_group("qib_axes", ""),
-    inline = TRUE
-  )
-})
-
-output$ui_qib_check <- renderUI({
-  req(input$qib_type)
-  if (input$qib_type == "scatter") {
-    ind <- 1:3
-  } else if (input$qib_type == "box") {
-    ind <- 3
-  } else if (input$qib_type == "surface") {
-    ind <- 4
-  } else {
-    ind <- c()
-  }
-  
-  if (!input$qib_type %in% c("scatter", "box")) {
-    r_state$qib_check <<- gsub("jitter", "", r_state$qib_check)
-  }
-  if (input$qib_type != "scatter") {
-    r_state$qib_check <<- gsub("line", "", r_state$qib_check)
-    r_state$qib_check <<- gsub("loess", "", r_state$qib_check)
-  }
-  
-  checkboxGroupInput(
-    "qib_check", NULL, qib_check[ind],
-    selected = state_group("qib_check", ""),
-    inline = TRUE
-  )
-})
-
-output$ui_qib_run <- renderUI({
-  req(input$dataset)
-  actionButton("qib_run", i18n$t("OneClick chart generation"), width = "100%", icon = icon("play", verify_fa = FALSE), class = "btn-success")
-})
-
-# output$ui_qib_labs <- renderUI({
-#   ## updates when dataset changes
-#   req(input$dataset)
-#   wellPanel(
-#     textAreaInput("qib_labs_title", NULL, "", placeholder = i18n$t("Title"), rows = 1),
-#     textAreaInput("qib_labs_subtitle", NULL, "", placeholder = i18n$t("Subtitle"), rows = 1),
-#     textAreaInput("qib_labs_caption", NULL, "", placeholder = i18n$t("Caption"), rows = 1),
-#     textAreaInput("qib_labs_y", NULL, "", placeholder = i18n$t("Y-label"), rows = 1),
-#     textAreaInput("qib_labs_x", NULL, "", placeholder = i18n$t("X-label"), rows = 1)
-#   )
-# })
-
-output$ui_qib_colors <- renderUI({
-  tagList(
-    conditionalPanel(
-      condition = "input.qib_type == 'bar' ||
-                   input.qib_type == 'dist' ||
-                   input.qib_type == 'box' ||
-                   input.qib_type == 'density'",
-      selectInput(
-        "qib_fillcol", i18n$t("Fill color:"),
-        choices = colors(),
-        selected = state_single("qib_fillcol", colors(), "blue")
-      )
-    ),
-    conditionalPanel(
-      condition = "input.qib_type == 'dist' ||
-                   input.qib_type == 'density' ||
-                   input.qib_type == 'box' ||
-                   input.qib_type == 'scatter' ||
-                   input.qib_type == 'line'",
-      selectInput(
-        "qib_linecol", i18n$t("Line color:"),
-        choices = colors(),
-        selected = state_single("qib_linecol", colors(), "black")
-      )
-    ),
-    conditionalPanel(
-      condition = "input.qib_type == 'scatter' ||
-                   input.qib_type == 'line' ||
-                   input.qib_type == 'box'",
-      selectInput(
-        "qib_pointcol", i18n$t("Point color:"),
-        choices = colors(),
-        selected = state_single("qib_pointcol", colors(), "black")
-      )
-    )
-  )
-})
-
-run_refresh(
-  qib_args, "qib",
-  init = c("xvar", "yvar"), label = i18n$t("OneClick chart generation"), relabel = i18n$t("Update plot"),
-  inputs = c("labs_title", "labs_subtitle", "labs_caption", "labs_y", "labs_x")
-)
-
-
-output$ui_quickgen_basic <- renderUI({
-  tagList(
-    wellPanel(
-      uiOutput("ui_qgb_run")
-    ),
-    checkboxInput("qgb_details_table", i18n$t("Table"), state_init("qgb_details_table", FALSE)),
-    conditionalPanel(
-      "input.qgb_details_table == true",
-      wellPanel(
-        uiOutput("ui_qgb_vars"),
-        uiOutput("ui_qgb_byvar"),
-        uiOutput("ui_qgb_top"),
-        # returnTextAreaInput("qgb_tab_slice",
-        #                     label = i18n$t("Table slice (rows):"),
-        #                     rows = 1,
-        #                     value = state_init("qgb_tab_slice"),
-        #                     placeholder = i18n$t("e.g., 1:5 and press return")
-        # ),
-        uiOutput("ui_qgb_fun"),
-        numericInput("qgb_dec", label = i18n$t("Decimals:"), value = state_init("qgb_dec", 3), min = 0),
-        tags$table(
-          tags$td(uiOutput("ui_qgb_name")),
-          tags$td(actionButton("qgb_store", i18n$t("Store"), icon = icon("plus", verify_fa = FALSE)), class = "top")
-        )
-      ),
-    ),
-    wellPanel(
-      uiOutput("ui_qib_run")
-    ),
-    checkboxInput("qib_details_chart", i18n$t("Chart"), state_init("qib_details_chart", FALSE)),
-    conditionalPanel(
-      "input.qib_details_chart == true",
-      wellPanel(
-        uiOutput("ui_qib_type"),
-        conditionalPanel(
-          "input.qib_type == 'scatter'",
-          uiOutput("ui_qib_nrobs")
-        ),
-        conditionalPanel(
-          condition = "input.qib_type != 'dist' && input.qib_type != 'density'",
-          uiOutput("ui_qib_yvar"),
-          conditionalPanel(
-            "input.qib_yvar != undefined && input.qib_yvar != null && input.qib_yvar.length > 1",
-            uiOutput("ui_qib_comby")
-          )
-        ),
-        uiOutput("ui_qib_xvar"),
-        conditionalPanel(
-          "input.qib_type == 'dist' || input.qib_type == 'density'",
-          conditionalPanel(
-            "input.qib_xvar != undefined && input.qib_xvar != null && input.qib_xvar.length > 1",
-            uiOutput("ui_qib_combx")
-          )
-        ),
-        # uiOutput("ui_qib_facet_row"),
-        # uiOutput("ui_qib_facet_col"),
-        # conditionalPanel(
-        #   condition = "input.qib_type == 'bar' ||
-        #                input.qib_type == 'dist' ||
-        #                input.qib_type == 'density' ||
-        #                input.qib_type == 'surface'",
-        #   uiOutput("ui_qib_fill")
-        # ),
-        # conditionalPanel(
-        #   condition = "input.qib_type == 'scatter' ||
-        #                input.qib_type == 'line' ||
-        #                input.qib_type == 'box'",
-        #   uiOutput("ui_qib_color")
-        # ),
-        # conditionalPanel(
-        #   condition = "input.qib_type == 'scatter'",
-        #   uiOutput("ui_qib_size")
-        # ),
-        conditionalPanel(
-          condition = "input.qib_type == 'bar' ||
-                       input.qib_type == 'scatter' ||
-                       input.qib_type == 'line'",
-          selectInput(
-            "qib_fun", i18n$t("Function:"),
-            choices = getOption("radiant.functions"),
-            selected = state_single("qib_fun", getOption("radiant.functions"), "mean")
-          )
-        ),
-        # conditionalPanel(
-        #   condition = "input.qib_type == 'scatter' ||
-        #                input.qib_type == 'line' ||
-        #                input.qib_type == 'surface' ||
-        #                input.qib_type == 'box'",
-        #   uiOutput("ui_qib_check")
-        # ),
-        # uiOutput("ui_qib_axes"),
-        conditionalPanel(
-          condition = "input.qib_type == 'dist'",
-          sliderInput(
-            "qib_bins",
-            label = i18n$t("Number of bins:"),
-            value = state_init("qib_bins", 10),
-            min = 2, max = 50, step = 1
-          )
-        ),
-        conditionalPanel(
-          "input.qib_type == 'density' ||
-           input.qib_type == 'dist' && (input.qib_axes && input.qib_axes.indexOf('density')) >= 0 ||
-           (input.qib_type == 'scatter' && (input.qib_check && input.qib_check.indexOf('loess') >= 0))",
-          sliderInput(
-            "qib_smooth",
-            label = i18n$t("Smooth:"),
-            value = state_init("qib_smooth", 1),
-            min = 0.1, max = 3, step = .1
-          )
-        )
-      )
-    ),
-    # checkboxInput("qib_details_labels", i18n$t("Labels"), state_init("qib_details_labels", FALSE)),
-    # conditionalPanel(
-    #   "input.qib_details_labels == true",
-    #   uiOutput("ui_qib_labs")
-    # ),
-    checkboxInput("qib_details_style", i18n$t("Style"), state_init("qib_details_style", FALSE)),
-    conditionalPanel(
-      "input.qib_details_style == true",
-      wellPanel(
-        selectInput(
-          "qib_theme", i18n$t("Plot theme:"),
-          choices = qib_theme,
-          selected = state_single("qib_theme", qib_theme, "theme_gray")
-        ),
-        numericInput(
-          "qib_base_size", i18n$t("Base font size:"),
-          value = state_init("qib_base_size", 11)
-        ),
-        selectInput(
-          "qib_base_family", i18n$t("Font family:"),
-          choices = qib_base_family,
-          selected = state_single("qib_base_family", qib_base_family, "helvetica")
-        ),
-        uiOutput("ui_qib_colors"),
-        sliderInput(
-          "qib_alpha",
-          label = i18n$t("Opacity:"),
-          value = state_init("qib_alpha", .5),
-          min = 0, max = 1, step = .01
-        ),
-        tags$table(
-          tags$td(
-            numericInput(
-              "qib_plot_height",
-              label = i18n$t("Plot height:"), min = 100,
-              max = 2000, step = 50,
-              value = state_init("qib_plot_height", r_info[["plot_height"]]),
-              width = "117px"
-            )
-          ),
-          tags$td(
-            numericInput(
-              "qib_plot_width",
-              label = i18n$t("Plot width:"), min = 100,
-              max = 2000, step = 50,
-              value = state_init("qib_plot_width", r_info[["plot_width"]]),
-              width = "117px"
-            ),
-            width = "100%"
-          )
-        )
-      )
-    ),
-    help_and_report(
-      modal_title = i18n$t("Generate descriptive statistics with one click"), fun_name = "quickgen_basic",
-      help_file = inclMD(file.path(getOption("radiant.path.quickgen"), "app/tools/help/quickgen_basic.md")),
-      lic = "by-sa"
-    )
-  )
-})
-
-qib_plot_width <- reactive({
-  if (is.empty(input$qib_plot_width)) r_info[["plot_width"]] else input$qib_plot_width
-})
-
-qib_plot_height <- eventReactive(
-  {
-    input$qib_run
-    input$qib_plot_height
-    input$qib_plot_width
-  },
-  {
-    if (is.empty(input$qib_plot_height)) {
-      r_info[["plot_height"]]
-    } else {
-      lx <- ifelse(not_available(input$qib_xvar) || isTRUE(input$qib_combx), 1, length(input$qib_xvar))
-      ly <- ifelse(not_available(input$qib_yvar) || input$qib_type %in% c("dist", "density") ||
-                     isTRUE(input$qib_comby), 1, length(input$qib_yvar))
-      nr <- lx * ly
-      if (nr > 1) {
-        (input$qib_plot_height / 2) * ceiling(nr / 2)
-      } else {
-        input$qib_plot_height
-      }
-    }
-  }
-)
-
-.quickgen <- eventReactive(input$qgb_run, {
-  if (not_available(input$qgb_vars) || is.null(input$qgb_top)) {
-    return()
-  } else if (!is.empty(input$qgb_byvar) && not_available(input$qgb_byvar)) {
-    return()
-  } else if (available(input$qgb_byvar) && any(input$qgb_byvar %in% input$qgb_vars)) {
-    return()
-  }
-  qgbi <- qgb_inputs()
-  qgbi$envir <- r_data
-  sshhr(do.call(explore, qgbi))
-})
-
-observeEvent(input$qgb_search_columns, {
-  r_state$qgb_search_columns <<- input$qgb_search_columns
-})
-
-observeEvent(input$qgb_state, {
-  r_state$qgb_state <<- input$qgb_state
-})
-
-
-qgb_reset <- function(var, ncol) {
-  if (!identical(r_state[[var]], input[[var]])) {
-    r_state[[var]] <<- input[[var]]
-    r_state$qgb_state <<- list()
-    r_state$qgb_search_columns <<- rep("", ncol)
-  }
-}
-
-output$qgb_tab <- DT::renderDataTable({
-  input$qgb_run
-  withProgress(message = i18n$t("Generating explore table"), value = 1, {
-    isolate({
-      qgb <- .quickgen()
-      req(!is.null(qgb))
-      qgb$shiny <- TRUE
-      
-      ## resetting DT when changes occur
-      nc <- ncol(qgb$tab)
-      qgb_reset("qgb_vars", nc)
-      qgb_reset("qgb_byvar", nc)
-      qgb_reset("qgb_fun", nc)
-      if (!is.null(r_state$qgb_top) &&
-          !is.null(input$qgb_top) &&
-          !identical(r_state$qgb_top, input$qgb_top)) {
-        r_state$qgb_top <<- input$qgb_top
-        r_state$qgb_state <<- list()
-        r_state$qgb_search_columns <<- rep("", nc)
-      }
-      
-      searchCols <- lapply(r_state$qgb_search_columns, function(x) list(search = x))
-      order <- r_state$qgb_state$order
-      pageLength <- r_state$qgb_state$length
-    })
-    
-    caption <- if (is.empty(input$qgb_tab_slice)) NULL else glue("Table slice {input$expl_tab_slice} will be applied on Download, Store, or Report")
-    dtab(
-      qgb,
-      dec = input$qgb_dec, searchCols = searchCols, order = order,
-      pageLength = pageLength,
-      caption = caption
-    )
-  })
-})
-
-dl_qgb_tab <- function(path) {
-  dat <- try(.quickgen(), silent = TRUE)
-  if (inherits(dat, "try-error") || is.null(dat)) {
-    write.csv(tibble::tibble("Data" = "[Empty]"), path, row.names = FALSE)
-    return()
-  }
-  
-  rows <- input$qgb_rows_all
-  tmp  <- if (is.null(rows)) dat$tab else dat$tab[rows, , drop = FALSE]
-  
-  if (is.null(tmp) || nrow(tmp) == 0) {
-    write.csv(tibble::tibble("Data" = "[Empty]"), path, row.names = FALSE)
-  } else {
-    write.csv(tmp, path, row.names = FALSE)
-  }
-}
-
-
-output$qib_chart <- renderPlot(
-  {
-    req(input$qib_type)
-    if (not_available(input$qib_xvar)) {
-      if (!input$qib_type %in% c("box", "line")) {
-        return(
-          plot(
-            x = 1, type = "n",
-            main = " ",
-            axes = FALSE, xlab = "", ylab = "", cex.main = .9
-          )
-        )
-      }
-    }
-    .qib_chart() %>%
-      (function(x) {
-        if (is.empty(x) || is.character(x)) {
-          plot(x = 1, type = "n", main = paste0("\n", x), axes = FALSE, xlab = "", ylab = "", cex.main = .9)
-        } else if (length(x) > 0) {
-          print(x)
-        }
-      })
-  },
-  width = qib_plot_width,
-  height = qib_plot_height,
-  res = 96
-)
-
-.qib_chart <- eventReactive(input$qib_run, {
-  req(input$qib_type)
-  if (input$qib_type == "scatter") req(input$qib_nrobs)
-  
-  ## need dependency on ..
-  req(input$qib_plot_height && input$qib_plot_width)
-  
-  if (not_available(input$qib_xvar) && !input$qib_type %in% c("box", "line")) {
-    return()
-  } else if (input$qib_type %in% c("scatter", "line", "box", "bar", "surface") && not_available(input$qib_yvar)) {
-    return(i18n$t("No Y-variable provided for a plot that requires one"))
-  } else if (input$qib_type == "box" && !all(input$qib_xvar %in% groupable_vars())) {
-    return()
-  }
-  
-  ## waiting for comby and/or combx to be updated
-  if (input$qib_type %in% c("dist", "density")) {
-    if (isTRUE(input$qib_comby)) {
-      return()
-    }
-    if (length(input$qib_xvar) > 1 && is.null(input$qib_combx)) {
-      return()
-    }
-  } else {
-    if (isTRUE(input$qib_combx)) {
-      return()
-    }
-    if (length(input$qib_yvar) > 1 && is.null(input$qib_comby)) {
-      return()
-    }
-  }
-  
-  #req(!is.null(input$qib_color) || !is.null(input$qib_fill))
-  qibi <- qib_inputs()
-  qibi$dataset <- input$dataset 
-  qibi$shiny <- TRUE
-  qibi$envir <- r_data
-  qibi$color    <- "none"
-  qibi$fill     <- "none"
-  qibi$facet_row <- "."
-  qibi$facet_col <- "."
-  withProgress(message = i18n$t("Making plot"), value = 1, {
-    do.call(visualize, qibi)
-  })
-})
-
-observeEvent(input$qgb_store, {
-  req(input$qgb_name)
-  dat <- .quickgen()
-  if (is.null(dat)) {
-    return()
-  }
-  dataset <- fix_names(input$qgb_name)
-  if (input$qgb_name != dataset) {
-    updateTextInput(session, inputId = "qgb_name", value = dataset)
-  }
-  rows <- input$qgb_rows_all
-  tmp  <- if (is.null(rows)) dat$tab else dat$tab[rows, , drop = FALSE]
-  r_data[[dataset]] <- tmp
-  register(dataset)
-  updateSelectInput(session, "dataset", selected = input$dataset)
-
-  showModal(
-    modalDialog(
-      title = i18n$t("Data Stored"),
-      span(
-        i18n$t("Dataset was successfully added to the datasets dropdown. Add code to Report > Rmd or Report > R to (re)create the results by clicking the report icon on the bottom left of your screen.")
-      ),
-      footer = modalButton(i18n$t("OK")),
-      size = "m",
-      easyClose = TRUE
-    )
-  )
-})
-
-qgb_report <- function() {
-  ## get the state of the dt table
-  ts <- dt_state("qgb_tab")
-  xcmd <- "# summary(result)\ndtab(result"
-  if (!is.empty(input$qgb_dec, 3)) {
-    xcmd <- paste0(xcmd, ", dec = ", input$qgb_dec)
-  }
-  if (!is.empty(r_state$qgb_state$length, 10)) {
-    xcmd <- paste0(xcmd, ", pageLength = ", r_state$qgb_state$length)
-  }
-  xcmd <- paste0(xcmd, ", caption = \"\") %>% render()")
-  if (!is.empty(input$qgb_name)) {
-    dataset <- fix_names(input$qgb_name)
-    if (input$qgb_name != dataset) {
-      updateTextInput(session, inputId = "qgb_name", value = dataset)
-    }
-    xcmd <- paste0(xcmd, "\n", dataset, " <- result$tab\nregister(\"", dataset, "\")")
-  }
-  
-  inp_main <- clean_args(qgb_inputs(), qgb_args)
-  if (ts$tabsort != "") inp_main <- c(inp_main, tabsort = ts$tabsort)
-  if (ts$tabfilt != "") inp_main <- c(inp_main, tabfilt = ts$tabfilt)
-  if (is.empty(inp_main$rows)) {
-    inp_main$rows <- NULL
-  }
-  if (is.empty(input$qgb_tab_slice)) {
-    inp_main <- c(inp_main, nr = Inf)
-  } else {
-    inp_main$tabslice <- input$qgb_tab_slice
-  }
-  
-  inp_out <- list(clean_args(qgb_sum_inputs(), qgb_sum_args[-1]))
-  
-  update_report(
-    inp_main = inp_main,
-    fun_name = "qgb",
-    inp_out = inp_out,
-    outputs = c(),
-    figs = FALSE,
-    xcmd = xcmd
-  )
-}
-
-qib_report <- function() {
-  ## resetting hidden elements to default values
-  vi <- qib_inputs()
-  if (input$qib_type != "dist") {
-    vi$bins <- qib_args$bins
-  }
-  if (input$qib_type %in% c("dist", "density")) {
-    vi$yvar <- qib_args$yvar
-  }
-  if (!input$qib_type %in% c("density", "scatter", "dist") ||
-      !("loess" %in% input$qib_check || "density" %in% input$qib_axes || input$qib_type == "density")) {
-    vi$smooth <- qib_args$smooth
-  }
-  if (!input$qib_type %in% c("scatter", "box") && "jitter" %in% input$qib_check) {
-    vi$check <- base::setdiff(vi$check, "jitter")
-  }
-  if (input$qib_type != "scatter") {
-    vi$size <- "none"
-    vi$nrobs <- NULL
-  } else {
-    vi$nrobs <- as_integer(vi$nrobs)
-  }
-  if (!input$qib_type %in% c("scatter", "line", "box")) {
-    vi$color <- NULL
-  }
-  if (!input$qib_type %in% c("bar", "dist", "density", "surface")) {
-    vi$fill <- NULL
-  }
-  
-  if (!input$qib_type %in% c("bar", "dist", "box", "density")) {
-    vi$fillcol <- "blue"
-  }
-  if (!input$qib_type %in% c("dist", "density", "box", "scatter", "line")) {
-    vi$linecol <- "black"
-  }
-  if (!input$qib_type %in% c("box", "scatter", "line")) {
-    vi$pointcol <- "black"
-  }
-  
-  if (!input$qib_type %in% c("bar", "line", "scatter")) {
-    vi$fun <- "mean"
-  }
-  if (is.empty(input$data_rows)) {
-    vi$rows <- NULL
-  }
-  
-  inp_main <- c(clean_args(vi, qib_args), custom = FALSE)
-  
-  update_report(
-    inp_main = inp_main,
-    fun_name = "qib_chart",
-    outputs = character(0),
-    pre_cmd = "",
-    figs = TRUE,
-    fig.width = qib_plot_width(),
-    fig.height = qib_plot_height()
-  )
-}
-
-download_handler(
-  id = "dl_qgb_tab",
-  fun = dl_qgb_tab,
-  fn = function() paste0(input$dataset, "_tab"),
-  type = "csv"
-)
-
-download_handler(
-  id = "dlp_qib_chart",
-  fun = download_handler_plot,
-  fn = function() paste0(input$dataset, "_chart"),
-  type = "png",
-  caption = i18n$t("Save visualize plot"),
-  plot = .qib_chart,
-  width = qib_plot_width,
-  height = qib_plot_height
-)
-
-
-observeEvent(input$qgb_report, {
-  r_info[["latest_screenshot"]] <- NULL
-  qgb_report()
-})
-
-observeEvent(input$qgb_screenshot, {
-  r_info[["latest_screenshot"]] <- NULL
-  radiant_screenshot_modal("modal_qgb_screenshot")
-})
-
-observeEvent(input$modal_qgb_screenshot, {
-  qgb_report()
-  removeModal()
-})
-
-observeEvent(input$qib_report, {
-  r_info[["latest_screenshot"]] <- NULL
-  qib_report()
-})
-
-observeEvent(input$qib_screenshot, {
-  r_info[["latest_screenshot"]] <- NULL
-  radiant_screenshot_modal("modal_qib_screenshot")
-})
-
-observeEvent(input$modal_qib_screenshot, {
-  qib_report()
-  removeModal()
-})
-
-# 全选功能
-observeEvent(input$qgb_select_all, {
-  r_funs <- getOption("radiant.functions")
-  if (!is.null(r_funs)) {
-    updateCheckboxGroupInput(session, "qgb_fun", selected = r_funs)
-  }
-})
-
-# 全不选功能
-observeEvent(input$qgb_deselect_all, {
-  updateCheckboxGroupInput(session, "qgb_fun", selected = character(0))
-})
-
-# 反选功能
-observeEvent(input$qgb_invert_selection, {
-  current <- input$qgb_fun %||% character(0)
-  r_funs <- getOption("radiant.functions")
-  if (!is.null(r_funs)) {
-    new_selection <- setdiff(r_funs, current)
-    updateCheckboxGroupInput(session, "qgb_fun", selected = new_selection)
-  }
-})
-
-output$quickgen_basic <- renderUI({
-  stat_tab_panel(
-    menu = i18n$t("Oneclick generation > Generate descriptive statistics"),
-    tool = i18n$t("Generate descriptive statistics with one click"),
-    tool_ui = "ui_quickgen_basic",
-    output_panels = tagList(
-      tabPanel(
-        title = i18n$t("Table"),
-        download_link("dl_qgb_tab"),br(),
-        DT::dataTableOutput("qgb_tab"),
-        tags$hr(),
-        htmlOutput("qgb_desc_text", inline = FALSE)
-      ),
-      tabPanel(
-        title = i18n$t("Chart"),
-        download_link("dlp_qib_chart"), br(),
-        plotOutput("qib_chart", width = "100%", height = "auto"),
-        tags$hr(),
-        htmlOutput("qib_desc_text", inline = FALSE)
-      )
-    )
-  )
-})
-
-## ---------- 表格的描述文字 ----------
-output$qgb_desc_text <- renderUI({
-  dat <- tryCatch(.quickgen(), error = function(e) NULL)
-  txt <- if (!is.null(dat) && !is.null(dat$tab)) {
-    make_desc_text(dat$tab)
-  } else {
-    " "
-  }
-  HTML(markdown::markdownToHTML(text = txt, fragment.only = TRUE))
-})
-
-## ---------- 图表的描述文字 ----------
-output$qib_desc_text <- renderUI({
-  df <- tryCatch({
-    qibi <- qib_inputs()
-    qibi$envir <- r_data
-    qibi$dataset <- input$dataset
-    qibi$shiny <- TRUE
-    res <- do.call(visualize, qibi)
-    res$data
-  }, error = function(e) NULL)
-  
-  txt <- if (!is.null(df)) make_desc_text(df) else " "
-  HTML(markdown::markdownToHTML(text = txt, fragment.only = TRUE))
-})
\ No newline at end of file
diff --git a/radiant.quickgen/inst/app/tools/analysis/quickgen_basic_ui.R b/radiant.quickgen/inst/app/tools/analysis/quickgen_basic_ui.R
index 9d84af288c148b983300a3ff6b45109c4362f244..d033c6daa3f002f23c9c28b63c297520643ebfd0 100644
--- a/radiant.quickgen/inst/app/tools/analysis/quickgen_basic_ui.R
+++ b/radiant.quickgen/inst/app/tools/analysis/quickgen_basic_ui.R
@@ -1,3 +1,8 @@
+safe_is_empty <- function(x) {
+  if (is.null(x) || !is.character(x)) return(TRUE)
+  is.empty(x)
+}
+
 make_desc_text <- function(df) {
   if (is.null(df) || nrow(df) == 0) return(i18n$t("No data available"))
   num_cols <- sapply(df, is.numeric)
@@ -68,7 +73,7 @@ qib_add_labs <- function() {
   lab_list <- list()
   for (l in qib_labs) {
     inp <- input[[paste0("qib_labs_", l)]]
-    if (!is.empty(inp)) lab_list[[l]] <- inp
+    if (!safe_is_empty(inp)) lab_list[[l]] <- inp
   }
   lab_list
 }
@@ -402,7 +407,7 @@ output$ui_qib_axes <- renderUI({
   } else if (input$qib_type %in% c("bar", "box")) {
     ind <- c(1, 3)
   }
-  if (!is.empty(input$qib_facet_row, ".") || !is.empty(input$qib_facet_col, ".")) ind <- c(ind, 4)
+  if (!safe_is_empty(input$qib_facet_row, ".") || !safe_is_empty(input$qib_facet_col, ".")) ind <- c(ind, 4)
   if (input$qib_type == "bar") ind <- c(ind, 6)
   
   checkboxGroupInput(
@@ -676,7 +681,7 @@ output$ui_quickgen_basic <- renderUI({
 })
 
 qib_plot_width <- reactive({
-  if (is.empty(input$qib_plot_width)) r_info[["plot_width"]] else input$qib_plot_width
+  if (safe_is_empty(input$qib_plot_width)) r_info[["plot_width"]] else input$qib_plot_width
 })
 
 qib_plot_height <- eventReactive(
@@ -686,7 +691,7 @@ qib_plot_height <- eventReactive(
     input$qib_plot_width
   },
   {
-    if (is.empty(input$qib_plot_height)) {
+    if (safe_is_empty(input$qib_plot_height)) {
       r_info[["plot_height"]]
     } else {
       lx <- ifelse(not_available(input$qib_xvar) || isTRUE(input$qib_combx), 1, length(input$qib_xvar))
@@ -786,77 +791,49 @@ dl_qgb_tab <- function(path) {
 }
 
 
-output$qib_chart <- renderPlot(
-  {
-    req(input$qib_type)
-    if (not_available(input$qib_xvar)) {
-      if (!input$qib_type %in% c("box", "line")) {
-        return(
-          plot(
-            x = 1, type = "n",
-            main = " ",
-            axes = FALSE, xlab = "", ylab = "", cex.main = .9
-          )
-        )
-      }
-    }
-    .qib_chart() %>%
-      (function(x) {
-        if (is.empty(x) || is.character(x)) {
-          plot(x = 1, type = "n", main = paste0("\n", x), axes = FALSE, xlab = "", ylab = "", cex.main = .9)
-        } else if (length(x) > 0) {
-          print(x)
-        }
-      })
-  },
-  width = qib_plot_width,
-  height = qib_plot_height,
-  res = 96
-)
+output$qib_chart <- renderPlot({
+  req(input$qib_type)
+  p <- .qib_chart()
+  if (is.null(p)) return(NULL)
+  print(p)
+}, width = qib_plot_width, height = qib_plot_height, res = 96)
 
 .qib_chart <- eventReactive(input$qib_run, {
   req(input$qib_type)
   if (input$qib_type == "scatter") req(input$qib_nrobs)
-  
-  ## need dependency on ..
   req(input$qib_plot_height && input$qib_plot_width)
   
   if (not_available(input$qib_xvar) && !input$qib_type %in% c("box", "line")) {
-    return()
-  } else if (input$qib_type %in% c("scatter", "line", "box", "bar", "surface") && not_available(input$qib_yvar)) {
-    return(i18n$t("No Y-variable provided for a plot that requires one"))
-  } else if (input$qib_type == "box" && !all(input$qib_xvar %in% groupable_vars())) {
-    return()
+    return(NULL)
+  }
+  if (input$qib_type %in% c("scatter", "line", "box", "bar", "surface") && not_available(input$qib_yvar)) {
+    return(NULL)
+  }
+  if (input$qib_type == "box" && !all(input$qib_xvar %in% groupable_vars())) {
+    return(NULL)
   }
   
-  ## waiting for comby and/or combx to be updated
+  ## 等待 combx / comby 更新
   if (input$qib_type %in% c("dist", "density")) {
-    if (isTRUE(input$qib_comby)) {
-      return()
-    }
-    if (length(input$qib_xvar) > 1 && is.null(input$qib_combx)) {
-      return()
-    }
+    if (isTRUE(input$qib_comby)) return(NULL)
+    if (length(input$qib_xvar) > 1 && is.null(input$qib_combx)) return(NULL)
   } else {
-    if (isTRUE(input$qib_combx)) {
-      return()
-    }
-    if (length(input$qib_yvar) > 1 && is.null(input$qib_comby)) {
-      return()
-    }
+    if (isTRUE(input$qib_combx)) return(NULL)
+    if (length(input$qib_yvar) > 1 && is.null(input$qib_comby)) return(NULL)
   }
   
-  #req(!is.null(input$qib_color) || !is.null(input$qib_fill))
   qibi <- qib_inputs()
-  qibi$dataset <- input$dataset 
-  qibi$shiny <- TRUE
-  qibi$envir <- r_data
-  qibi$color    <- "none"
-  qibi$fill     <- "none"
+  qibi$dataset <- input$dataset
+  qibi$shiny   <- TRUE
+  qibi$envir   <- r_data
+  qibi$color   <- "none"
+  qibi$fill    <- "none"
   qibi$facet_row <- "."
   qibi$facet_col <- "."
+  
   withProgress(message = i18n$t("Making plot"), value = 1, {
-    do.call(visualize, qibi)
+    p <- do.call(visualize, qibi)
+    if (is.character(p)) return(NULL) else p  
   })
 })
 
@@ -875,7 +852,7 @@ observeEvent(input$qgb_store, {
   r_data[[dataset]] <- tmp
   register(dataset)
   updateSelectInput(session, "dataset", selected = input$dataset)
-
+  
   showModal(
     modalDialog(
       title = i18n$t("Data Stored"),
@@ -889,154 +866,95 @@ observeEvent(input$qgb_store, {
   )
 })
 
-qgb_report <- function() {
-  ## get the state of the dt table
-  ts <- dt_state("qgb_tab")
-  xcmd <- "# summary(result)\ndtab(result"
-  if (!is.empty(input$qgb_dec, 3)) {
-    xcmd <- paste0(xcmd, ", dec = ", input$qgb_dec)
-  }
-  if (!is.empty(r_state$qgb_state$length, 10)) {
-    xcmd <- paste0(xcmd, ", pageLength = ", r_state$qgb_state$length)
-  }
+download_handler(
+  id = "dl_qgb_tab",
+  fun = dl_qgb_tab,
+  fn = function() paste0(input$dataset, "_tab"),
+  type = "csv"
+)
+
+download_handler(
+  id = "dlp_qib_chart",
+  fun = download_handler_plot,
+  fn = function() paste0(input$dataset, "_chart"),
+  type = "png",
+  caption = i18n$t("Save visualize plot"),
+  plot = .qib_chart,
+  width = qib_plot_width,
+  height = qib_plot_height
+)
+
+quickgen_basic_report <- function() {
+  req(input$qgb_vars, input$qib_type)
+  
+  ##--------------  表 格 部 分  --------------
+  tabsort <- if (!is.null(input$qgb_state$order))
+    paste0("order = ", jsonlite::toJSON(input$qgb_state$order)) else ""
+  tabfilt <- if (!is.null(input$qgb_search_columns))
+    paste0("searchCols = ", jsonlite::toJSON(lapply(input$qgb_search_columns, function(x) list(search = x)))) else ""
+  xcmd <- "# quickgen table: descriptive statistics\ndtab(result"
+  if (!is.empty(input$qgb_dec, 3))     xcmd <- paste0(xcmd, ", dec = ", input$qgb_dec)
+  if (!is.empty(r_state$qgb_state$length, 10)) xcmd <- paste0(xcmd, ", pageLength = ", r_state$qgb_state$length)
+  if (nzchar(tabsort))  xcmd <- paste0(xcmd, ", ", tabsort)
+  if (nzchar(tabfilt))  xcmd <- paste0(xcmd, ", ", tabfilt)
   xcmd <- paste0(xcmd, ", caption = \"\") %>% render()")
   if (!is.empty(input$qgb_name)) {
     dataset <- fix_names(input$qgb_name)
-    if (input$qgb_name != dataset) {
+    if (input$qgb_name != dataset)
       updateTextInput(session, inputId = "qgb_name", value = dataset)
-    }
     xcmd <- paste0(xcmd, "\n", dataset, " <- result$tab\nregister(\"", dataset, "\")")
   }
-  
   inp_main <- clean_args(qgb_inputs(), qgb_args)
-  if (ts$tabsort != "") inp_main <- c(inp_main, tabsort = ts$tabsort)
-  if (ts$tabfilt != "") inp_main <- c(inp_main, tabfilt = ts$tabfilt)
-  if (is.empty(inp_main$rows)) {
-    inp_main$rows <- NULL
-  }
-  if (is.empty(input$qgb_tab_slice)) {
-    inp_main <- c(inp_main, nr = Inf)
-  } else {
-    inp_main$tabslice <- input$qgb_tab_slice
-  }
+  if (is.empty(inp_main$rows)) inp_main$rows <- NULL
+  if (!is.empty(input$qgb_tab_slice)) inp_main$tabslice <- input$qgb_tab_slice
   
-  inp_out <- list(clean_args(qgb_sum_inputs(), qgb_sum_args[-1]))
-  
-  update_report(
-    inp_main = inp_main,
-    fun_name = "qgb",
-    inp_out = inp_out,
-    outputs = c(),
-    figs = FALSE,
-    xcmd = xcmd
-  )
-}
-
-qib_report <- function() {
-  ## resetting hidden elements to default values
+  ##--------------  图 形 部 分  --------------
   vi <- qib_inputs()
-  if (input$qib_type != "dist") {
-    vi$bins <- qib_args$bins
-  }
-  if (input$qib_type %in% c("dist", "density")) {
-    vi$yvar <- qib_args$yvar
-  }
+  if (input$qib_type != "dist")  vi$bins <- qib_args$bins
+  if (input$qib_type %in% c("dist", "density"))  vi$yvar <- qib_args$yvar
   if (!input$qib_type %in% c("density", "scatter", "dist") ||
-      !("loess" %in% input$qib_check || "density" %in% input$qib_axes || input$qib_type == "density")) {
+      !("loess" %in% input$qib_check || "density" %in% input$qib_axes || input$qib_type == "density"))
     vi$smooth <- qib_args$smooth
-  }
-  if (!input$qib_type %in% c("scatter", "box") && "jitter" %in% input$qib_check) {
+  if (!input$qib_type %in% c("scatter", "box") && "jitter" %in% input$qib_check)
     vi$check <- base::setdiff(vi$check, "jitter")
-  }
   if (input$qib_type != "scatter") {
-    vi$size <- "none"
+    vi$size  <- "none"
     vi$nrobs <- NULL
   } else {
     vi$nrobs <- as_integer(vi$nrobs)
   }
-  if (!input$qib_type %in% c("scatter", "line", "box")) {
-    vi$color <- NULL
-  }
-  if (!input$qib_type %in% c("bar", "dist", "density", "surface")) {
-    vi$fill <- NULL
-  }
+  if (!input$qib_type %in% c("scatter", "line", "box"))  vi$color <- NULL
+  if (!input$qib_type %in% c("bar", "dist", "density", "surface"))  vi$fill <- NULL
+  if (!input$qib_type %in% c("bar", "dist", "box", "density"))  vi$fillcol <- "blue"
+  if (!input$qib_type %in% c("dist", "density", "box", "scatter", "line"))  vi$linecol <- "black"
+  if (!input$qib_type %in% c("box", "scatter", "line"))  vi$pointcol <- "black"
+  if (!input$qib_type %in% c("bar", "line", "scatter"))  vi$fun <- "mean"
+  if (safe_is_empty(input$data_rows))  vi$rows <- NULL
   
-  if (!input$qib_type %in% c("bar", "dist", "box", "density")) {
-    vi$fillcol <- "blue"
-  }
-  if (!input$qib_type %in% c("dist", "density", "box", "scatter", "line")) {
-    vi$linecol <- "black"
-  }
-  if (!input$qib_type %in% c("box", "scatter", "line")) {
-    vi$pointcol <- "black"
-  }
-  
-  if (!input$qib_type %in% c("bar", "line", "scatter")) {
-    vi$fun <- "mean"
-  }
-  if (is.empty(input$data_rows)) {
-    vi$rows <- NULL
-  }
-  
-  inp_main <- c(clean_args(vi, qib_args), custom = FALSE)
+  inp_main <- c(inp_main, clean_args(vi, qib_args), custom = FALSE)
   
+  ##--------------  一次性写进 Report  --------------
   update_report(
-    inp_main = inp_main,
-    fun_name = "qib_chart",
-    outputs = character(0),
-    pre_cmd = "",
-    figs = TRUE,
-    fig.width = qib_plot_width(),
+    inp_main   = inp_main,
+    fun_name   = "quickgen_basic",      # 统一事件名
+    outputs    = character(0),
+    pre_cmd    = "",
+    figs       = TRUE,                  # 需要插图
+    fig.width  = qib_plot_width(),
     fig.height = qib_plot_height()
   )
 }
 
-download_handler(
-  id = "dl_qgb_tab",
-  fun = dl_qgb_tab,
-  fn = function() paste0(input$dataset, "_tab"),
-  type = "csv"
-)
-
-download_handler(
-  id = "dlp_qib_chart",
-  fun = download_handler_plot,
-  fn = function() paste0(input$dataset, "_chart"),
-  type = "png",
-  caption = i18n$t("Save visualize plot"),
-  plot = .qib_chart,
-  width = qib_plot_width,
-  height = qib_plot_height
-)
-
-
-observeEvent(input$qgb_report, {
-  r_info[["latest_screenshot"]] <- NULL
-  qgb_report()
-})
-
-observeEvent(input$qgb_screenshot, {
-  r_info[["latest_screenshot"]] <- NULL
-  radiant_screenshot_modal("modal_qgb_screenshot")
-})
-
-observeEvent(input$modal_qgb_screenshot, {
-  qgb_report()
-  removeModal()
-})
-
-observeEvent(input$qib_report, {
+observeEvent(input$quickgen_basic_report, {
   r_info[["latest_screenshot"]] <- NULL
-  qib_report()
+  quickgen_basic_report()
 })
-
-observeEvent(input$qib_screenshot, {
+observeEvent(input$quickgen_basic_screenshot, {
   r_info[["latest_screenshot"]] <- NULL
-  radiant_screenshot_modal("modal_qib_screenshot")
+  radiant_screenshot_modal("modal_quickgen_basic_screenshot")
 })
-
-observeEvent(input$modal_qib_screenshot, {
-  qib_report()
+observeEvent(input$modal_quickgen_basic_screenshot, {
+  quickgen_basic_report()
   removeModal()
 })
 
diff --git a/radiant.quickgen/inst/app/tools/help/quickgen_ai.md b/radiant.quickgen/inst/app/tools/help/quickgen_ai.md
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..983dea5822d7e7d5fed161d45abb9016e31d809a 100644
--- a/radiant.quickgen/inst/app/tools/help/quickgen_ai.md
+++ b/radiant.quickgen/inst/app/tools/help/quickgen_ai.md
@@ -0,0 +1,27 @@
+> 大模型生成描述性统计
+
+## 使用方法
+
+以下是 `大模型生成描述性统计`的使用方法。
+
+1.`数据对象`必须要有，且必须和数据集中的名字一致（大小写也一致）
+
+2.`图像类型`必须要有，比如分布图、散点图等。可以要求模型返回多张图表，需向模型明确。
+
+3.`生成代码`如果有误，或者想要修改，可以点击`编辑`按钮对R代码进行修改，保存后点击`运行`按钮即可。
+## 示例
+
+**1. 散点图**  
+请用diamonds画一个散点图，X轴是carat，Y轴是price，用color来区分颜色，并加上theme_bw()。  
+**2. 箱线图**  
+请用diamonds画箱线图，把price按cut分组，看看不同切工的价格分布。  
+**3. 直方图**  
+请用diamonds画carat的直方图，分面按clarity排布，bin宽度取0.1。  
+**4. 柱状图**  
+请用diamonds统计各color等级的数量，画一个柱状图，颜色按实际颜色填充。  
+**5. 密度图**  
+请用diamonds画出0.5~2克拉范围内，不同color的carat密度曲线，要求半透明重叠。  
+**6. 分组均值表**  
+请用diamonds按cut分组，计算每组price与carat的平均值、标准差，输出成表格。  
+**7. 价格对数-克拉线性拟合图**  
+请用diamonds画log(price)和carat的散点图，并加上回归直线，颜色按clarity区分，用theme_minimal()。  
\ No newline at end of file
diff --git a/set_path.R b/set_path.R
index 4f80e1b24b451b28d9e9ce4cdee496394d8f9970..391503e65d0f383dca7eff838d5b4b6630ea5832 100644
--- a/set_path.R
+++ b/set_path.R
@@ -1,4 +1,3 @@
-# 创建文件 /home/wuzekai/radiant/set_path.R
 cat <<'EOF' | sudo tee /home/wuzekai/radiant/set_path.R
 options(radiant.launch_dir = "/data")
 options(radiant.project_dir = "/data")