【问题标题】：determining total number of times distinct values 0 or 1 or na in each column in a data frame in R确定 R 中数据框中每列中不同值 0 或 1 或 na 的总次数
【发布时间】：2017-03-01 02:40:54
【问题描述】：

我有 15 列，我想按每列中的值按 0 或 1 或 na 分组。

我的数据集

A,B,C,D,E,F,G,H,I,J,K,L,M,N,O
0.0,0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,1.0
1.0,1.0,1.0,1.0,0.0,0.0,0.0,1.0,0.0,1.0,0.0,1.0,1.0,1.0,1.0
1.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,1.0,0.0,1.0,1.0,1.0,1.0
NA,1.0,0.0,0.0,NA,0.0,0.0,0.0,NA,NA,NA,NA,NA,NA,NA
1.0,1.0,1.0,1.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0
1.0,1.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0
1.0,1.0,1.0,1.0,1.0,0.0,1.0,1.0,0.0,1.0,1.0,1.0,1.0,1.0,1.0
1.0,1.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0,NA,NA,NA,NA,NA
1.0,1.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
1.0,1.0,1.0,1.0,0.0,1.0,0.0,0.0,NA,0.0,NA,NA,NA,NA,NA
1.0,1.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,1.0,1.0,1.0,0.0,1.0,1.0
1.0,1.0,1.0,1.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,1.0,1.0,0.0,1.0
1.0,1.0,1.0,1.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0,1.0,1.0,1.0
1.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0
1.0,1.0,1.0,1.0,0.0,1.0,0.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,0.0
0.0,0.0,0.0,0.0,0.0,NA,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
1.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,1.0,1.0,0.0,1.0,0.0,0.0,1.0
1.0,1.0,1.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0,1.0,0.0,0.0
1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0
1.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,1.0,1.0,1.0,0.0,1.0,0.0,1.0
0.0,1.0,1.0,0.0,0.0,0.0,NA,NA,NA,NA,NA,NA,NA,NA,NA
1.0,1.0,1.0,1.0,0.0,0.0,1.0,1.0,1.0,0.0,0.0,0.0,1.0,1.0,0.0
NA,NA,1.0,NA,NA,0.0,1.0,1.0,1.0,1.0,0.0,1.0,1.0,1.0,1.0
0.0,1.0,0.0,0.0,0.0,0.0,0.0,NA,0.0,0.0,NA,NA,NA,NA,NA

我希望输出是这样的：

    A  B  C  D  E  F  G  H  I  J  K  L  M  N  O
0   5  6  2  3  5  0  1  2  3  4  1  2  0  0  1
1   5  6  2  3  5  0  1  2  3  4  1  2  0  0  1
NA  5  6  2  3  5  0  1  2  3  4  1  2  0  0  1

【问题讨论】：

标签： r dataframe count counter

【解决方案1】：

我们可以遍历数据集并应用table 和useNA="always"

sapply(df1, table, useNA="always")

如果列中只有一个特定值，比如 1，则将其转换为 factor，levels 指定为 0 和 1

sapply(df1, function(x) table(factor(x, levels = 0:1), useNA = "always"))
#      A  B  C  D  E  F  G  H  I  J  K  L  M  N  O
#0     4  3  8  7 17 15 14 11 14 12 12 10  8 11  9
#1    19 21 17 17  6  9 10 12  8 11  8 10 12  9 11
#<NA>  2  1  0  1  2  1  1  2  3  2  5  5  5  5  5

【讨论】：

我忘记了因素位。谢谢