apply

Including the group name in the apply function pandas python

由 早过忘川 提交于 2020-05-25 09:35:14
问题 Is there away to specify to the groupby() call to use the group name in the apply() lambda function? Similar to if I iterate through groups I can get the group key via the following tuple decomposition: for group_name, subdf in temp_dataframe.groupby(level=0, axis=0): print group_name ...is there a way to also get the group name in the apply function, such as: temp_dataframe.groupby(level=0,axis=0).apply(lambda group_name, subdf: foo(group_name, subdf) How can I get the group name as an

Including the group name in the apply function pandas python

由 心已入冬 提交于 2020-05-25 09:34:35
问题 Is there away to specify to the groupby() call to use the group name in the apply() lambda function? Similar to if I iterate through groups I can get the group key via the following tuple decomposition: for group_name, subdf in temp_dataframe.groupby(level=0, axis=0): print group_name ...is there a way to also get the group name in the apply function, such as: temp_dataframe.groupby(level=0,axis=0).apply(lambda group_name, subdf: foo(group_name, subdf) How can I get the group name as an

what's the difference between 'call/apply' and 'bind' [duplicate]

由 让人想犯罪 __ 提交于 2020-05-24 08:15:37
问题 This question already has answers here : Javascript call() & apply() vs bind()? (20 answers) Closed 7 years ago . var obj = { x: 81, getX: function() { console.log( this.x) } }; var getX = obj.getX.bind(obj);//use obj as 'this'; getX();//81 var getX = function(){ obj.getX.apply(obj); } getX();//also 81 The use of bind and call/apply look very similar, I want to know what's the difference between them.The two getX Function above is the same? 回答1: bind returns a function which will act like the

what's the difference between 'call/apply' and 'bind' [duplicate]

由 跟風遠走 提交于 2020-05-24 08:15:27
问题 This question already has answers here : Javascript call() & apply() vs bind()? (20 answers) Closed 7 years ago . var obj = { x: 81, getX: function() { console.log( this.x) } }; var getX = obj.getX.bind(obj);//use obj as 'this'; getX();//81 var getX = function(){ obj.getX.apply(obj); } getX();//also 81 The use of bind and call/apply look very similar, I want to know what's the difference between them.The two getX Function above is the same? 回答1: bind returns a function which will act like the

Creating list of lists with summary statistics for input to summary_table() in R

由 。_饼干妹妹 提交于 2020-05-17 06:00:42
问题 I am following the instructions laid out here to create a clean table of summary statistics. In these instructions, the input to the summary_table() function is a list of lists, as shown here: our_summary1 <- list("Miles Per Gallon" = list("min" = ~ min(.data$mpg), "max" = ~ max(.data$mpg), "mean (sd)" = ~ qwraps2::mean_sd(.data$mpg)), "Displacement" = list("min" = ~ min(.data$disp), "median" = ~ median(.data$disp), "max" = ~ max(.data$disp), "mean (sd)" = ~ qwraps2::mean_sd(.data$disp)),

Running iterated regressions for data divided into N chunks in R

由 半世苍凉 提交于 2020-05-17 05:54:07
问题 I have a dataframe structured like the following: birthwt tobacco01 pscore pscoreblocks 3425 0 0.18 (0.177, 0.187] 3527 1 0.15 (0.158, 0.168] 1638 1 0.34 (0.335, 0.345] The birthwt column is a continuous variable measuring birth weight in grams. The tobacco01 column contains values of 0 or 1. The pscore column contains probability values between 0 and 1. The pscoreblocks takes the pscore column and breaks it down into 100 equally sized blocks. I am trying to find an efficient way to do the

nested sapply in R - breakdown

由 旧巷老猫 提交于 2020-04-18 05:44:18
问题 This post is related to my previous question about extracting data from nested lists, which has been answered. One of the answers contains a sapply function: usageExist <- sapply(garden$fruit, function(f){ sapply(garden$usage, '%in%', x = names(productFruit$type[[f]][["usage"]]))}) I am very new to data.table and apply functions and struggle to understand: what is happening in this particular line of code ? Why does cooking appear twice in the lists after running usageExists ? What is the

nested sapply in R - breakdown

由 丶灬走出姿态 提交于 2020-04-18 05:43:17
问题 This post is related to my previous question about extracting data from nested lists, which has been answered. One of the answers contains a sapply function: usageExist <- sapply(garden$fruit, function(f){ sapply(garden$usage, '%in%', x = names(productFruit$type[[f]][["usage"]]))}) I am very new to data.table and apply functions and struggle to understand: what is happening in this particular line of code ? Why does cooking appear twice in the lists after running usageExists ? What is the

How to use apply to change the elements of one dataframe based in the columns of another?

由 蹲街弑〆低调 提交于 2020-03-25 18:37:28
问题 I have a data frame where two columns mark the beginning and end of regions I need to manipulate in another data frame. Instead of applying a for I decided to create a logical vector with the rows I'm interested df <- data.frame(b=c(7,25,32,44),e=c(11,27,39,48),n=c('a','b','c','d')) logint <- rep(F,50) log_vec <- apply(df[,c('b','e')],1, function(x){logint[x['b']:x['e']] <- T;return(logint)}) However, the result a matrix with one column for each row of df . I know I can solve this with log

Scala 之 apply()

由 眉间皱痕 提交于 2020-03-10 07:34:22
学习Scala之前，在JavaScript里常使用apply()方法。 class Account private ( val id : Int , initialBalance : Double ) { private var balance = initialBalance } object Account { def newUniqueNumber ( ) : Int = { // 随便写的 9527 } def apply ( initialBalance : Double ) = new Account ( newUniqueNumber ( ) , initialBalance ) } object Main { def main ( args : Array [ String ] ) : Unit = { // 注意：没有new val acct = Account ( 1000.0 ) // a是一个长度为1的数组，第一个元素值为100 var a = Array ( 100 ) println ( "a.length=" + a . length ) println ( "a(0)=" + a ( 0 ) ) // b是一个长度为100的数组，数组里的元素都是null var b = new Array ( 100 ) println ( "b.length="
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