[英]R- count values in data.frame
df <- data.frame(row.names = c('ID1','ID2','ID3','ID4'),var1 = c(0,1,2,3),var2 = c(0,0,0,0),var3 = c(1,2,3,0),var4 = c('1','1','2','2'))
> df
var1 var2 var3 var4
ID1 0 0 1 1
ID2 1 0 2 1
ID3 2 0 3 2
ID4 3 0 0 2
I want df to look like this我希望 df 看起来像这样
var1 var2 var3 var4
0 1 4 1 0
1 1 0 1 2
2 1 0 1 2
3 1 0 1 0
So I want the values of df to be counted.所以我希望计算 df 的值。 The problem is, that not every value occurs in every column.
问题是,并非每个值都出现在每一列中。 I tried this
lapply(df,table)
but that returns a list which I cannot convert into a data.frame (because of said reason).我尝试了这个
lapply(df,table)
但它返回了一个我无法转换为 data.frame 的列表(由于上述原因)。 I could do it kind of manually with table(df$var1)
and bind everything together after doing that with every var, but that is boring.我可以使用
table(df$var1)
手动执行此操作,并在对每个 var 执行此操作后将所有内容绑定在一起,但这很无聊。 Can you find a better way?你能找到更好的方法吗?
Thanks;)谢谢;)
Call table
function with factor levels which are present in the entire dataset.调用
table
function 以及整个数据集中存在的因子水平。
sapply(df,function(x) table(factor(x, levels = 0:3)))
# var1 var2 var3 var4
#0 1 4 1 0
#1 1 0 1 2
#2 1 0 1 2
#3 1 0 1 0
If you don't know beforehand what levels your data can take, we can find it from data itself.如果您事先不知道您的数据可以达到什么级别,我们可以从数据本身中找到它。
vec <- unique(unlist(df))
sapply(df, function(x) table(factor(x, levels = vec)))
We could do this without any loop我们可以在没有任何循环的情况下做到这一点
table(c(col(df)), unlist(df))
# 0 1 2 3
# 1 1 1 1 1
# 2 4 0 0 0
# 3 1 1 1 1
# 4 0 2 2 0
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