extras/vtreatOnSpark.md
In WinVector/vtreat: A Statistically Sound 'data.frame' Processor/Conditioner
vtreat on Spark
base::date()
## [1] "Sat Dec 1 15:10:05 2018"
library("vtreat")
packageVersion("vtreat")
## [1] '1.3.3'
library("rquery")
packageVersion("rquery")
## [1] '1.2.1'
packageVersion("cdata")
## [1] '1.0.4'
packageVersion("sparklyr")
## [1] '0.9.1'
conf <- sparklyr::spark_config()
conf$sparklyr.log.console <- FALSE
conf$spark.yarn.am.cores <- 2
conf$spark.executor.cores <- 2
conf$spark.executor.memory <- "4G"
conf$spark.yarn.am.memory <- "4G"
conf$`sparklyr.shell.driver-memory` <- "4G"
conf$`sparklyr.shell.executor-memory` <- "4G"
conf$`spark.yarn.executor.memoryOverhead` <- "4G"
raw_connection <- sparklyr::spark_connect(version='2.2.0',
master = "local",
config = conf)
db_opts <- rq_connection_tests(raw_connection)
db <- rquery_db_info(connection = raw_connection,
is_dbi = TRUE,
connection_options = db_opts)
base::date()
## [1] "Sat Dec 1 15:10:26 2018"
base::date()
## [1] "Sat Dec 1 15:10:40 2018"
tmp_name_gen <- wrapr::mk_tmp_name_source("kddvtreat")
d <- db_td(db, "kdd2009") %.>%
extend_nse(., sample_col = random())
cat(format(d))
## table(`kdd2009`;
## Var1,
## Var2,
## Var3,
## Var4,
## Var5,
## Var6,
## Var7,
## Var8,
## Var9,
## Var10,
## Var11,
## Var12,
## Var13,
## Var14,
## Var15,
## Var16,
## Var17,
## Var18,
## Var19,
## Var20,
## ...) %.>%
## extend(.,
## sample_col := random())
#cat(to_sql(d, db))
d <- materialize(db, d, table_name = tmp_name_gen())
y_name <- "churn"
vars <- setdiff(column_names(d), c(y_name, "sample_col"))
d_train <- d %.>%
select_rows_nse(., sample_col <= 0.5) %.>%
materialize(db, ., table_name = tmp_name_gen())
d_test <- d %.>%
select_rows_nse(., sample_col > 0.9) %.>%
materialize(db, ., table_name = tmp_name_gen())
d_variable_design <- d %.>%
select_rows_nse(., (sample_col > 0.5) & (sample_col <= 0.9)) %.>%
materialize(db, ., table_name = tmp_name_gen())
base::date()
## [1] "Sat Dec 1 15:11:44 2018"
base::date()
## [1] "Sat Dec 1 15:11:44 2018"
cl = parallel::makeCluster(4)
print(length(vars))
## [1] 230
# design treatments in small groups to manage memory
vgroups <- split(vars, ceiling(seq_len(length(vars))/10))
treatment_plans <- lapply(vgroups,
function(vi) {
di <- d_variable_design %.>%
select_columns(., c(y_name, vi)) %.>%
execute(db, .)
vtreat::designTreatmentsC(di, vi, y_name, 1,
parallelCluster = cl,
verbose = FALSE)
})
base::date()
## [1] "Sat Dec 1 15:12:48 2018"
base::date()
## [1] "Sat Dec 1 15:12:48 2018"
# get unified scoreFrame
scoreFrame <- lapply(treatment_plans,
function(tpi) {
tpi$scoreFrame
})
scoreFrame <- do.call(rbind, scoreFrame)
base::date()
## [1] "Sat Dec 1 15:12:48 2018"
# try to get Bonferroni- corrected valid derived variables.
approximate_df <- length(vars) + nrow(scoreFrame)
theshold <- 1/(1 + approximate_df)
newvars <- scoreFrame$varName[ (scoreFrame$varMoves) &
(scoreFrame$sig < theshold) &
(scoreFrame$rsq >= 1.0e-3) ]
newvars <- unique(newvars)
print(length(newvars))
## [1] 122
base::date()
## [1] "Sat Dec 1 15:12:48 2018"
base::date()
## [1] "Sat Dec 1 15:12:48 2018"
col_sample <- execute(db, d_train, limit = 1L)
rqplan <- as_rquery_plan(treatment_plans, var_restriction = newvars)
if(FALSE) {
ops <- rquery_prepare(db, rqplan, d_train,
"dtrain_prepped",
col_sample = col_sample,
return_ops = TRUE)
cat(format(ops))
ops %.>%
rquery::op_diagram(.) %.>%
DiagrammeR::grViz(.)
# sql <- rquery::to_sql(ops, db)
# cat(sql)
}
base::date()
## [1] "Sat Dec 1 15:12:49 2018"
d_train <- rquery_prepare(db, rqplan, d_train,
tmp_name_gen(),
col_sample = col_sample,
temporary = TRUE,
overwrite = TRUE)
length(column_names(d_train))
## [1] 123
base::date()
## [1] "Sat Dec 1 15:13:28 2018"
# cdata::qlook(db, d_train$table_name)
# rquery::rlook(db, d_train$table_name)
d_train %.>%
orderby(., limit = 10) %.>%
execute(db, .) %.>%
str(., list.len = 10000)
## 'data.frame': 10 obs. of 123 variables:
## $ churn : num -1 -1 -1 -1 -1 -1 -1 -1 1 -1
## $ Var192_catP : num 0.004061 0.006318 0.000251 0.006318 0.005917 ...
## $ Var193_catP : num 0.146 0.146 0.146 0.146 0.146 ...
## $ Var193_catB : num -0.546 -0.546 -0.546 -0.546 -0.546 ...
## $ Var198_catP : num 1.30e-03 6.52e-04 1.20e-03 4.01e-04 2.51e-05 ...
## $ Var199_catP : num 0.011984 0.012234 0.000251 0.005766 0.016095 ...
## $ Var200_catP : num 2.51e-05 5.01e-05 2.51e-05 2.51e-05 2.51e-05 ...
## $ Var202_catP : num 2.01e-04 3.01e-04 1.15e-03 2.51e-05 1.50e-04 ...
## $ Var205_catP : num 0.639 0.639 0.231 0.231 0.639 ...
## $ Var205_catB : num -0.0705 -0.0705 -0.1865 -0.1865 -0.0705 ...
## $ Var206_catP : num 0.0144 0.0219 0.0588 0.0588 0.035 ...
## $ Var206_catB : num -0.0674 -0.6848 -0.6859 -0.6859 -0.1927 ...
## $ Var207_catP : num 0.699 0.699 0.699 0.699 0.699 ...
## $ Var207_catB : num 0.126 0.126 0.126 0.126 0.126 ...
## $ Var210_catP : num 0.952 0.952 0.952 0.952 0.952 ...
## $ Var210_catB : num -0.0305 -0.0305 -0.0305 -0.0305 -0.0305 ...
## $ Var212_catP : num 0.5841 0.1281 0.1281 0.1281 0.0137 ...
## $ Var212_catB : num 0.238 -0.557 -0.557 -0.557 -0.796 ...
## $ Var214_catP : num 2.51e-05 5.01e-05 2.51e-05 2.51e-05 2.51e-05 ...
## $ Var216_catB : num -0.233 -0.862 -0.313 -0.313 -0.667 ...
## $ Var217_catP : num 2.01e-04 5.01e-05 1.15e-03 2.51e-05 5.01e-05 ...
## $ Var218_catP : num 0.48 0.505 0.48 0.505 0.505 ...
## $ Var218_catB : num 0.146 -0.254 0.146 -0.254 -0.254 ...
## $ Var220_catP : num 1.30e-03 6.52e-04 1.20e-03 4.01e-04 2.51e-05 ...
## $ Var221_catP : num 0.737 0.737 0.737 0.737 0.737 ...
## $ Var221_catB : num 0.103 0.103 0.103 0.103 0.103 ...
## $ Var222_catP : num 1.30e-03 6.52e-04 1.20e-03 4.01e-04 2.51e-05 ...
## $ Var225_catP : num 0.207 0.219 0.207 0.219 0.219 ...
## $ Var225_catB : num -0.0792 -0.4271 -0.0792 -0.4271 -0.4271 ...
## $ Var226_catP : num 0.162 0.0276 0.06 0.0223 0.0938 ...
## $ Var226_catB : num 0.2437 0.0901 -0.2908 -0.0442 -0.1246 ...
## $ Var227_catP : num 0.701 0.701 0.701 0.701 0.701 ...
## $ Var227_catB : num 0.125 0.125 0.125 0.125 0.125 ...
## $ Var228_catP : num 0.0874 0.0874 0.0874 0.0874 0.0874 ...
## $ Var228_catB : num -0.388 -0.388 -0.388 -0.388 -0.388 ...
## $ Var229_catP : num 0.000652 0.000652 0.000652 0.000652 0.000652 ...
## $ Var229_catB : num 0.0981 0.0981 0.0981 0.0981 0.0981 ...
## $ Var6_isBAD : int 0 0 0 0 0 0 0 1 0 0
## $ Var7_clean : num 7 7 7 7 0 7 7 7 7 0
## $ Var13_clean : num 2968 632 528 400 348 ...
## $ Var21_isBAD : int 0 0 0 0 0 0 0 1 0 0
## $ Var22_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var25_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var28_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var35_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var38_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var44_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var65_clean : num 9 9 9 9 9 9 9 9 9 9
## $ Var72_clean : num 3 3 4.21 3 4.21 ...
## $ Var73_clean : num 126 118 126 106 132 90 100 100 80 82
## $ Var74_clean : num 490 7 28 35 0 224 140 168 189 0
## $ Var76_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var78_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var81_clean : num 115048 36041 1076211 146004 1692 ...
## $ Var81_isBAD : int 0 0 0 0 0 0 0 1 0 0
## $ Var83_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var85_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var112_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var113_clean : num -38397 -709072 44967 126870 -2135 ...
## $ Var119_isBAD : int 0 0 0 0 0 0 0 1 0 0
## $ Var123_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var126_clean : num -26 -18 -28 4 -0.409 ...
## $ Var126_isBAD : int 0 0 0 0 1 0 1 0 1 1
## $ Var132_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var133_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var134_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var140_clean : num 11845 205 1000 110 0 ...
## $ Var143_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var144_clean : num 36 18 18 9 9 ...
## $ Var144_isBAD : int 0 0 0 0 0 0 0 1 0 0
## $ Var153_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var160_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var163_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var173_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var181_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var189_clean : num 354 222 366 324 240 ...
## $ Var193_lev_x_2Knk1KF : int 1 1 1 1 1 0 0 0 0 0
## $ Var193_lev_x_RO12 : int 0 0 0 0 0 1 1 1 1 1
## $ Var198_lev_x_fhk21Ss : int 0 0 0 0 0 0 0 0 0 0
## $ Var200_lev_x_NA : int 0 0 0 0 0 1 0 0 1 0
## $ Var205_lev_x_09_Q : int 0 0 1 1 0 0 1 0 1 0
## $ Var205_lev_x_sJzTlal : int 0 0 0 0 0 1 0 1 0 1
## $ Var205_lev_x_VpdQ : int 1 1 0 0 1 0 0 0 0 0
## $ Var206_lev_x_hAFG : int 0 0 0 0 0 0 0 0 0 0
## $ Var206_lev_x_haYg : int 0 0 1 1 0 0 0 0 0 0
## $ Var206_lev_x_IYzP : int 0 0 0 0 0 0 0 0 0 1
## $ Var206_lev_x_NA : int 0 0 0 0 0 0 0 1 0 0
## $ Var206_lev_x_y6dw : int 0 0 0 0 0 0 0 0 0 0
## $ Var206_lev_x_zm5i : int 0 0 0 0 0 0 0 0 0 0
## $ Var207_lev_x_7M47J5GA0pTYIFxg5uy : int 0 0 0 0 0 0 0 0 0 0
## $ Var207_lev_x_DHn_WUyBhW_whjA88g9bvA64_: int 0 0 0 0 0 0 0 0 0 0
## $ Var207_lev_x_me75fM6ugJ : int 1 1 1 1 1 1 1 1 1 0
## $ Var210_lev_x_g5HH : int 0 0 0 0 0 0 0 0 1 0
## $ Var210_lev_x_uKAI : int 1 1 1 1 1 1 1 1 0 1
## $ Var211_lev_x_L84s : int 1 0 1 1 1 0 1 1 1 1
## $ Var211_lev_x_Mtgm : int 0 1 0 0 0 1 0 0 0 0
## $ Var212_lev_x_CrNX : int 0 0 0 0 0 0 0 0 0 0
## $ Var212_lev_x_NhsEn4L : int 1 0 0 0 0 1 1 1 0 0
## $ Var212_lev_x_XfqtO3UdzaXh_ : int 0 1 1 1 0 0 0 0 0 0
## $ Var214_lev_x_NA : int 0 0 0 0 0 1 0 0 1 0
## $ Var216_lev_x_XTbPUYD : int 0 1 0 0 0 0 0 0 0 0
## $ Var218_lev_x_cJvF : int 0 1 0 1 1 0 0 0 1 1
## $ Var218_lev_x_UYBR : int 1 0 1 0 0 1 1 1 0 0
## $ Var220_lev_x_4UxGlow : int 0 0 0 0 0 0 0 0 0 0
## $ Var221_lev_x_d0EEeJi : int 0 0 0 0 0 0 0 0 0 0
## $ Var221_lev_x_oslk : int 1 1 1 1 1 1 1 1 1 0
## $ Var221_lev_x_QKW8DRm : int 0 0 0 0 0 0 0 0 0 0
## $ Var221_lev_x_zCkv : int 0 0 0 0 0 0 0 0 0 1
## $ Var222_lev_x_catzS2D : int 0 0 0 0 0 0 0 0 0 0
## $ Var225_lev_x_ELof : int 0 1 0 1 1 0 0 0 0 1
## $ Var225_lev_x_NA : int 0 0 0 0 0 1 0 0 1 0
## $ Var226_lev_x_FSa2 : int 1 0 0 0 0 0 0 0 0 0
## $ Var227_lev_x_nIGXDli : int 0 0 0 0 0 0 0 0 0 0
## $ Var227_lev_x_RAYp : int 1 1 1 1 1 1 1 1 1 0
## $ Var227_lev_x_ZI9m : int 0 0 0 0 0 0 0 0 0 0
## $ Var228_lev_x_55YFVY9 : int 1 1 1 1 1 0 0 0 0 0
## $ Var228_lev_x_F2FyR07IdsN7I : int 0 0 0 0 0 1 1 1 1 0
## $ Var228_lev_x_ib5G6X1eUxUn6 : int 0 0 0 0 0 0 0 0 0 0
## $ Var228_lev_x_iyHGyLCEkQ : int 0 0 0 0 0 0 0 0 0 0
## $ Var228_lev_x_TCU50_Yjmm6GIBZ0lL_ : int 0 0 0 0 0 0 0 0 0 0
## $ Var229_lev_x_am7c : int 0 0 0 0 0 0 0 0 0 0
## $ Var229_lev_x_mj86 : int 0 0 0 0 0 0 0 0 0 0
## $ Var229_lev_x_NA : int 0 0 0 0 0 0 0 0 0 0
base::date()
## [1] "Sat Dec 1 15:13:29 2018"
WinVector/vtreat documentation built on Aug. 29, 2023, 4:49 a.m.
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vtreat on Spark
base::date()
## [1] "Sat Dec 1 15:10:05 2018"
library("vtreat")
packageVersion("vtreat")
## [1] '1.3.3'
library("rquery")
packageVersion("rquery")
## [1] '1.2.1'
packageVersion("cdata")
## [1] '1.0.4'
packageVersion("sparklyr")
## [1] '0.9.1'
conf <- sparklyr::spark_config()
conf$sparklyr.log.console <- FALSE
conf$spark.yarn.am.cores <- 2
conf$spark.executor.cores <- 2
conf$spark.executor.memory <- "4G"
conf$spark.yarn.am.memory <- "4G"
conf$`sparklyr.shell.driver-memory` <- "4G"
conf$`sparklyr.shell.executor-memory` <- "4G"
conf$`spark.yarn.executor.memoryOverhead` <- "4G"
raw_connection <- sparklyr::spark_connect(version='2.2.0',
master = "local",
config = conf)
db_opts <- rq_connection_tests(raw_connection)
db <- rquery_db_info(connection = raw_connection,
is_dbi = TRUE,
connection_options = db_opts)
base::date()
## [1] "Sat Dec 1 15:10:26 2018"
base::date()
## [1] "Sat Dec 1 15:10:40 2018"
tmp_name_gen <- wrapr::mk_tmp_name_source("kddvtreat")
d <- db_td(db, "kdd2009") %.>%
extend_nse(., sample_col = random())
cat(format(d))
## table(`kdd2009`;
## Var1,
## Var2,
## Var3,
## Var4,
## Var5,
## Var6,
## Var7,
## Var8,
## Var9,
## Var10,
## Var11,
## Var12,
## Var13,
## Var14,
## Var15,
## Var16,
## Var17,
## Var18,
## Var19,
## Var20,
## ...) %.>%
## extend(.,
## sample_col := random())
#cat(to_sql(d, db))
d <- materialize(db, d, table_name = tmp_name_gen())
y_name <- "churn"
vars <- setdiff(column_names(d), c(y_name, "sample_col"))
d_train <- d %.>%
select_rows_nse(., sample_col <= 0.5) %.>%
materialize(db, ., table_name = tmp_name_gen())
d_test <- d %.>%
select_rows_nse(., sample_col > 0.9) %.>%
materialize(db, ., table_name = tmp_name_gen())
d_variable_design <- d %.>%
select_rows_nse(., (sample_col > 0.5) & (sample_col <= 0.9)) %.>%
materialize(db, ., table_name = tmp_name_gen())
base::date()
## [1] "Sat Dec 1 15:11:44 2018"
base::date()
## [1] "Sat Dec 1 15:11:44 2018"
cl = parallel::makeCluster(4)
print(length(vars))
## [1] 230
# design treatments in small groups to manage memory
vgroups <- split(vars, ceiling(seq_len(length(vars))/10))
treatment_plans <- lapply(vgroups,
function(vi) {
di <- d_variable_design %.>%
select_columns(., c(y_name, vi)) %.>%
execute(db, .)
vtreat::designTreatmentsC(di, vi, y_name, 1,
parallelCluster = cl,
verbose = FALSE)
})
base::date()
## [1] "Sat Dec 1 15:12:48 2018"
base::date()
## [1] "Sat Dec 1 15:12:48 2018"
# get unified scoreFrame
scoreFrame <- lapply(treatment_plans,
function(tpi) {
tpi$scoreFrame
})
scoreFrame <- do.call(rbind, scoreFrame)
base::date()
## [1] "Sat Dec 1 15:12:48 2018"
# try to get Bonferroni- corrected valid derived variables.
approximate_df <- length(vars) + nrow(scoreFrame)
theshold <- 1/(1 + approximate_df)
newvars <- scoreFrame$varName[ (scoreFrame$varMoves) &
(scoreFrame$sig < theshold) &
(scoreFrame$rsq >= 1.0e-3) ]
newvars <- unique(newvars)
print(length(newvars))
## [1] 122
base::date()
## [1] "Sat Dec 1 15:12:48 2018"
base::date()
## [1] "Sat Dec 1 15:12:48 2018"
col_sample <- execute(db, d_train, limit = 1L)
rqplan <- as_rquery_plan(treatment_plans, var_restriction = newvars)
if(FALSE) {
ops <- rquery_prepare(db, rqplan, d_train,
"dtrain_prepped",
col_sample = col_sample,
return_ops = TRUE)
cat(format(ops))
ops %.>%
rquery::op_diagram(.) %.>%
DiagrammeR::grViz(.)
# sql <- rquery::to_sql(ops, db)
# cat(sql)
}
base::date()
## [1] "Sat Dec 1 15:12:49 2018"
d_train <- rquery_prepare(db, rqplan, d_train,
tmp_name_gen(),
col_sample = col_sample,
temporary = TRUE,
overwrite = TRUE)
length(column_names(d_train))
## [1] 123
base::date()
## [1] "Sat Dec 1 15:13:28 2018"
# cdata::qlook(db, d_train$table_name)
# rquery::rlook(db, d_train$table_name)
d_train %.>%
orderby(., limit = 10) %.>%
execute(db, .) %.>%
str(., list.len = 10000)
## 'data.frame': 10 obs. of 123 variables:
## $ churn : num -1 -1 -1 -1 -1 -1 -1 -1 1 -1
## $ Var192_catP : num 0.004061 0.006318 0.000251 0.006318 0.005917 ...
## $ Var193_catP : num 0.146 0.146 0.146 0.146 0.146 ...
## $ Var193_catB : num -0.546 -0.546 -0.546 -0.546 -0.546 ...
## $ Var198_catP : num 1.30e-03 6.52e-04 1.20e-03 4.01e-04 2.51e-05 ...
## $ Var199_catP : num 0.011984 0.012234 0.000251 0.005766 0.016095 ...
## $ Var200_catP : num 2.51e-05 5.01e-05 2.51e-05 2.51e-05 2.51e-05 ...
## $ Var202_catP : num 2.01e-04 3.01e-04 1.15e-03 2.51e-05 1.50e-04 ...
## $ Var205_catP : num 0.639 0.639 0.231 0.231 0.639 ...
## $ Var205_catB : num -0.0705 -0.0705 -0.1865 -0.1865 -0.0705 ...
## $ Var206_catP : num 0.0144 0.0219 0.0588 0.0588 0.035 ...
## $ Var206_catB : num -0.0674 -0.6848 -0.6859 -0.6859 -0.1927 ...
## $ Var207_catP : num 0.699 0.699 0.699 0.699 0.699 ...
## $ Var207_catB : num 0.126 0.126 0.126 0.126 0.126 ...
## $ Var210_catP : num 0.952 0.952 0.952 0.952 0.952 ...
## $ Var210_catB : num -0.0305 -0.0305 -0.0305 -0.0305 -0.0305 ...
## $ Var212_catP : num 0.5841 0.1281 0.1281 0.1281 0.0137 ...
## $ Var212_catB : num 0.238 -0.557 -0.557 -0.557 -0.796 ...
## $ Var214_catP : num 2.51e-05 5.01e-05 2.51e-05 2.51e-05 2.51e-05 ...
## $ Var216_catB : num -0.233 -0.862 -0.313 -0.313 -0.667 ...
## $ Var217_catP : num 2.01e-04 5.01e-05 1.15e-03 2.51e-05 5.01e-05 ...
## $ Var218_catP : num 0.48 0.505 0.48 0.505 0.505 ...
## $ Var218_catB : num 0.146 -0.254 0.146 -0.254 -0.254 ...
## $ Var220_catP : num 1.30e-03 6.52e-04 1.20e-03 4.01e-04 2.51e-05 ...
## $ Var221_catP : num 0.737 0.737 0.737 0.737 0.737 ...
## $ Var221_catB : num 0.103 0.103 0.103 0.103 0.103 ...
## $ Var222_catP : num 1.30e-03 6.52e-04 1.20e-03 4.01e-04 2.51e-05 ...
## $ Var225_catP : num 0.207 0.219 0.207 0.219 0.219 ...
## $ Var225_catB : num -0.0792 -0.4271 -0.0792 -0.4271 -0.4271 ...
## $ Var226_catP : num 0.162 0.0276 0.06 0.0223 0.0938 ...
## $ Var226_catB : num 0.2437 0.0901 -0.2908 -0.0442 -0.1246 ...
## $ Var227_catP : num 0.701 0.701 0.701 0.701 0.701 ...
## $ Var227_catB : num 0.125 0.125 0.125 0.125 0.125 ...
## $ Var228_catP : num 0.0874 0.0874 0.0874 0.0874 0.0874 ...
## $ Var228_catB : num -0.388 -0.388 -0.388 -0.388 -0.388 ...
## $ Var229_catP : num 0.000652 0.000652 0.000652 0.000652 0.000652 ...
## $ Var229_catB : num 0.0981 0.0981 0.0981 0.0981 0.0981 ...
## $ Var6_isBAD : int 0 0 0 0 0 0 0 1 0 0
## $ Var7_clean : num 7 7 7 7 0 7 7 7 7 0
## $ Var13_clean : num 2968 632 528 400 348 ...
## $ Var21_isBAD : int 0 0 0 0 0 0 0 1 0 0
## $ Var22_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var25_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var28_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var35_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var38_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var44_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var65_clean : num 9 9 9 9 9 9 9 9 9 9
## $ Var72_clean : num 3 3 4.21 3 4.21 ...
## $ Var73_clean : num 126 118 126 106 132 90 100 100 80 82
## $ Var74_clean : num 490 7 28 35 0 224 140 168 189 0
## $ Var76_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var78_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var81_clean : num 115048 36041 1076211 146004 1692 ...
## $ Var81_isBAD : int 0 0 0 0 0 0 0 1 0 0
## $ Var83_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var85_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var112_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var113_clean : num -38397 -709072 44967 126870 -2135 ...
## $ Var119_isBAD : int 0 0 0 0 0 0 0 1 0 0
## $ Var123_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var126_clean : num -26 -18 -28 4 -0.409 ...
## $ Var126_isBAD : int 0 0 0 0 1 0 1 0 1 1
## $ Var132_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var133_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var134_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var140_clean : num 11845 205 1000 110 0 ...
## $ Var143_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var144_clean : num 36 18 18 9 9 ...
## $ Var144_isBAD : int 0 0 0 0 0 0 0 1 0 0
## $ Var153_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var160_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var163_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var173_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var181_isBAD : int 0 0 0 0 0 0 0 0 0 0
## $ Var189_clean : num 354 222 366 324 240 ...
## $ Var193_lev_x_2Knk1KF : int 1 1 1 1 1 0 0 0 0 0
## $ Var193_lev_x_RO12 : int 0 0 0 0 0 1 1 1 1 1
## $ Var198_lev_x_fhk21Ss : int 0 0 0 0 0 0 0 0 0 0
## $ Var200_lev_x_NA : int 0 0 0 0 0 1 0 0 1 0
## $ Var205_lev_x_09_Q : int 0 0 1 1 0 0 1 0 1 0
## $ Var205_lev_x_sJzTlal : int 0 0 0 0 0 1 0 1 0 1
## $ Var205_lev_x_VpdQ : int 1 1 0 0 1 0 0 0 0 0
## $ Var206_lev_x_hAFG : int 0 0 0 0 0 0 0 0 0 0
## $ Var206_lev_x_haYg : int 0 0 1 1 0 0 0 0 0 0
## $ Var206_lev_x_IYzP : int 0 0 0 0 0 0 0 0 0 1
## $ Var206_lev_x_NA : int 0 0 0 0 0 0 0 1 0 0
## $ Var206_lev_x_y6dw : int 0 0 0 0 0 0 0 0 0 0
## $ Var206_lev_x_zm5i : int 0 0 0 0 0 0 0 0 0 0
## $ Var207_lev_x_7M47J5GA0pTYIFxg5uy : int 0 0 0 0 0 0 0 0 0 0
## $ Var207_lev_x_DHn_WUyBhW_whjA88g9bvA64_: int 0 0 0 0 0 0 0 0 0 0
## $ Var207_lev_x_me75fM6ugJ : int 1 1 1 1 1 1 1 1 1 0
## $ Var210_lev_x_g5HH : int 0 0 0 0 0 0 0 0 1 0
## $ Var210_lev_x_uKAI : int 1 1 1 1 1 1 1 1 0 1
## $ Var211_lev_x_L84s : int 1 0 1 1 1 0 1 1 1 1
## $ Var211_lev_x_Mtgm : int 0 1 0 0 0 1 0 0 0 0
## $ Var212_lev_x_CrNX : int 0 0 0 0 0 0 0 0 0 0
## $ Var212_lev_x_NhsEn4L : int 1 0 0 0 0 1 1 1 0 0
## $ Var212_lev_x_XfqtO3UdzaXh_ : int 0 1 1 1 0 0 0 0 0 0
## $ Var214_lev_x_NA : int 0 0 0 0 0 1 0 0 1 0
## $ Var216_lev_x_XTbPUYD : int 0 1 0 0 0 0 0 0 0 0
## $ Var218_lev_x_cJvF : int 0 1 0 1 1 0 0 0 1 1
## $ Var218_lev_x_UYBR : int 1 0 1 0 0 1 1 1 0 0
## $ Var220_lev_x_4UxGlow : int 0 0 0 0 0 0 0 0 0 0
## $ Var221_lev_x_d0EEeJi : int 0 0 0 0 0 0 0 0 0 0
## $ Var221_lev_x_oslk : int 1 1 1 1 1 1 1 1 1 0
## $ Var221_lev_x_QKW8DRm : int 0 0 0 0 0 0 0 0 0 0
## $ Var221_lev_x_zCkv : int 0 0 0 0 0 0 0 0 0 1
## $ Var222_lev_x_catzS2D : int 0 0 0 0 0 0 0 0 0 0
## $ Var225_lev_x_ELof : int 0 1 0 1 1 0 0 0 0 1
## $ Var225_lev_x_NA : int 0 0 0 0 0 1 0 0 1 0
## $ Var226_lev_x_FSa2 : int 1 0 0 0 0 0 0 0 0 0
## $ Var227_lev_x_nIGXDli : int 0 0 0 0 0 0 0 0 0 0
## $ Var227_lev_x_RAYp : int 1 1 1 1 1 1 1 1 1 0
## $ Var227_lev_x_ZI9m : int 0 0 0 0 0 0 0 0 0 0
## $ Var228_lev_x_55YFVY9 : int 1 1 1 1 1 0 0 0 0 0
## $ Var228_lev_x_F2FyR07IdsN7I : int 0 0 0 0 0 1 1 1 1 0
## $ Var228_lev_x_ib5G6X1eUxUn6 : int 0 0 0 0 0 0 0 0 0 0
## $ Var228_lev_x_iyHGyLCEkQ : int 0 0 0 0 0 0 0 0 0 0
## $ Var228_lev_x_TCU50_Yjmm6GIBZ0lL_ : int 0 0 0 0 0 0 0 0 0 0
## $ Var229_lev_x_am7c : int 0 0 0 0 0 0 0 0 0 0
## $ Var229_lev_x_mj86 : int 0 0 0 0 0 0 0 0 0 0
## $ Var229_lev_x_NA : int 0 0 0 0 0 0 0 0 0 0
base::date()
## [1] "Sat Dec 1 15:13:29 2018"
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