用R计算最常用的行数(Count most frequent word in row by R)

有一张桌子如下所示

Name Mon Tue Wed Thu Fri Sat Sun 1 John Apple Orange Apple Banana Apple Apple Orange 2 Ricky Banana Apple Banana Banana Banana Banana Apple 3 Alex Apple Orange Orange Apple Apple Orange Orange 4 Robbin Apple Apple Apple Apple Apple Banana Banana 5 Sunny Banana Banana Apple Apple Apple Banana Banana

所以，我想为每个人计算最频繁的水果，并在新栏中添加这些值。

例如。

Name Mon Tue Wed Thu Fri Sat Sun Max_Acc Count 1 John Apple Orange Apple Banana Apple Apple Orange Apple 4 2 Ricky Banana Apple Banana Banana Banana Banana Apple Banana 5 3 Alex Apple Orange Orange Apple Apple Orange Orange Orange 4 4 Robbin Apple Apple Apple Apple Apple Banana Banana Apple 5 5 Sunny Banana Banana Apple Apple Apple Banana Banana Banana 4

我在寻找行时面临问题。 我可以使用table()函数在列中找到Frequency。

>table(df$Mon) Apple Banana 3 2

但在这里，我想要新专栏中最常见水果的名称。

There is a table shown below

Name Mon Tue Wed Thu Fri Sat Sun 1 John Apple Orange Apple Banana Apple Apple Orange 2 Ricky Banana Apple Banana Banana Banana Banana Apple 3 Alex Apple Orange Orange Apple Apple Orange Orange 4 Robbin Apple Apple Apple Apple Apple Banana Banana 5 Sunny Banana Banana Apple Apple Apple Banana Banana

So , I want to count the most frequent Fruit for each person and add those value in new column.

For example.

Name Mon Tue Wed Thu Fri Sat Sun Max_Acc Count 1 John Apple Orange Apple Banana Apple Apple Orange Apple 4 2 Ricky Banana Apple Banana Banana Banana Banana Apple Banana 5 3 Alex Apple Orange Orange Apple Apple Orange Orange Orange 4 4 Robbin Apple Apple Apple Apple Apple Banana Banana Apple 5 5 Sunny Banana Banana Apple Apple Apple Banana Banana Banana 4

I am facing problem in finding rows. I can find Frequency in column by using table() function.

>table(df$Mon) Apple Banana 3 2

But here i want name of most frequent fruit in new column.

最满意答案

如果我们需要对应于max “Count”的“Count”和“Names”，我们遍历数据集的行（使用apply with MARGIN = 1 ），使用table获取频率，从中提取最大值和与最大值对应的names ， rbind it和cbind与原始数据集。

cbind(df1, do.call(rbind, apply(df1[-1], 1, function(x) { x1 <- table(x) data.frame(Count = max(x1), Names=names(x1)[which.max(x1)])}))) # Name Mon Tue Wed Thu Fri Sat Sun Count Names #1 John Apple Orange Apple Banana Apple Apple Orange 4 Apple #2 Ricky Banana Apple Banana Banana Banana Banana Apple 5 Banana #3 Alex Apple Orange Orange Apple Apple Orange Orange 4 Orange #4 Robbin Apple Apple Apple Apple Apple Banana Banana 5 Apple #5 Sunny Banana Banana Apple Apple Apple Banana Banana 4 Banana

或者我们可以使用data.table

library(data.table) setDT(df1)[, c("Names", "Count") := {tbl <- table(unlist(.SD)) .(names(tbl)[which.max(tbl)], max(tbl))}, by = Name]

If we need the "Count" and "Names" corresponding to the max "Count", we loop through the rows of the dataset (using apply with MARGIN = 1), use table to get the frequency, extract the maximum value from it and the names corresponding to the maximum value, rbind it and cbind with the original dataset.

cbind(df1, do.call(rbind, apply(df1[-1], 1, function(x) { x1 <- table(x) data.frame(Count = max(x1), Names=names(x1)[which.max(x1)])}))) # Name Mon Tue Wed Thu Fri Sat Sun Count Names #1 John Apple Orange Apple Banana Apple Apple Orange 4 Apple #2 Ricky Banana Apple Banana Banana Banana Banana Apple 5 Banana #3 Alex Apple Orange Orange Apple Apple Orange Orange 4 Orange #4 Robbin Apple Apple Apple Apple Apple Banana Banana 5 Apple #5 Sunny Banana Banana Apple Apple Apple Banana Banana 4 Banana

Or we can use data.table

library(data.table) setDT(df1)[, c("Names", "Count") := {tbl <- table(unlist(.SD)) .(names(tbl)[which.max(tbl)], max(tbl))}, by = Name]用R计算最常用的行数(Count most frequent word in row by R)

有一张桌子如下所示

Name Mon Tue Wed Thu Fri Sat Sun 1 John Apple Orange Apple Banana Apple Apple Orange 2 Ricky Banana Apple Banana Banana Banana Banana Apple 3 Alex Apple Orange Orange Apple Apple Orange Orange 4 Robbin Apple Apple Apple Apple Apple Banana Banana 5 Sunny Banana Banana Apple Apple Apple Banana Banana

所以，我想为每个人计算最频繁的水果，并在新栏中添加这些值。

例如。

Name Mon Tue Wed Thu Fri Sat Sun Max_Acc Count 1 John Apple Orange Apple Banana Apple Apple Orange Apple 4 2 Ricky Banana Apple Banana Banana Banana Banana Apple Banana 5 3 Alex Apple Orange Orange Apple Apple Orange Orange Orange 4 4 Robbin Apple Apple Apple Apple Apple Banana Banana Apple 5 5 Sunny Banana Banana Apple Apple Apple Banana Banana Banana 4

我在寻找行时面临问题。 我可以使用table()函数在列中找到Frequency。

>table(df$Mon) Apple Banana 3 2

但在这里，我想要新专栏中最常见水果的名称。

There is a table shown below

Name Mon Tue Wed Thu Fri Sat Sun 1 John Apple Orange Apple Banana Apple Apple Orange 2 Ricky Banana Apple Banana Banana Banana Banana Apple 3 Alex Apple Orange Orange Apple Apple Orange Orange 4 Robbin Apple Apple Apple Apple Apple Banana Banana 5 Sunny Banana Banana Apple Apple Apple Banana Banana

So , I want to count the most frequent Fruit for each person and add those value in new column.

For example.

Name Mon Tue Wed Thu Fri Sat Sun Max_Acc Count 1 John Apple Orange Apple Banana Apple Apple Orange Apple 4 2 Ricky Banana Apple Banana Banana Banana Banana Apple Banana 5 3 Alex Apple Orange Orange Apple Apple Orange Orange Orange 4 4 Robbin Apple Apple Apple Apple Apple Banana Banana Apple 5 5 Sunny Banana Banana Apple Apple Apple Banana Banana Banana 4

I am facing problem in finding rows. I can find Frequency in column by using table() function.

>table(df$Mon) Apple Banana 3 2

But here i want name of most frequent fruit in new column.

最满意答案

如果我们需要对应于max “Count”的“Count”和“Names”，我们遍历数据集的行（使用apply with MARGIN = 1 ），使用table获取频率，从中提取最大值和与最大值对应的names ， rbind it和cbind与原始数据集。

cbind(df1, do.call(rbind, apply(df1[-1], 1, function(x) { x1 <- table(x) data.frame(Count = max(x1), Names=names(x1)[which.max(x1)])}))) # Name Mon Tue Wed Thu Fri Sat Sun Count Names #1 John Apple Orange Apple Banana Apple Apple Orange 4 Apple #2 Ricky Banana Apple Banana Banana Banana Banana Apple 5 Banana #3 Alex Apple Orange Orange Apple Apple Orange Orange 4 Orange #4 Robbin Apple Apple Apple Apple Apple Banana Banana 5 Apple #5 Sunny Banana Banana Apple Apple Apple Banana Banana 4 Banana

或者我们可以使用data.table

library(data.table) setDT(df1)[, c("Names", "Count") := {tbl <- table(unlist(.SD)) .(names(tbl)[which.max(tbl)], max(tbl))}, by = Name]

If we need the "Count" and "Names" corresponding to the max "Count", we loop through the rows of the dataset (using apply with MARGIN = 1), use table to get the frequency, extract the maximum value from it and the names corresponding to the maximum value, rbind it and cbind with the original dataset.

cbind(df1, do.call(rbind, apply(df1[-1], 1, function(x) { x1 <- table(x) data.frame(Count = max(x1), Names=names(x1)[which.max(x1)])}))) # Name Mon Tue Wed Thu Fri Sat Sun Count Names #1 John Apple Orange Apple Banana Apple Apple Orange 4 Apple #2 Ricky Banana Apple Banana Banana Banana Banana Apple 5 Banana #3 Alex Apple Orange Orange Apple Apple Orange Orange 4 Orange #4 Robbin Apple Apple Apple Apple Apple Banana Banana 5 Apple #5 Sunny Banana Banana Apple Apple Apple Banana Banana 4 Banana

Or we can use data.table

library(data.table) setDT(df1)[, c("Names", "Count") := {tbl <- table(unlist(.SD)) .(names(tbl)[which.max(tbl)], max(tbl))}, by = Name]