Python/Pandas数据框-返回列名 [英] Python/Pandas dataframe - return column name
问题描述
是否有一种方法可以将列的名称/标题返回到pandas数据框中的字符串中?我想使用具有相同前缀的数据行.数据帧头看起来像这样:
Is there a way to return the name/header of a column into a string in a pandas dataframe? I want to work with a row of data which has the same prefix. The dataframe header looks like this:
col_00 | col_01 | ... | col_51 | bc_00 | cd_00 | cd_01 | ... | cd_90
我想对每行应用一个函数,但只能分别从col_00
到col_51
以及从cd_00
到cd_90
.为此,我想我会将列名称收集到一个列表中,例如fe. to_work_with
将是以前缀'col'开头的列的列表,将该功能应用于df[to_work_with]
.然后,我将更改to_work_with
,它将包含以'cd'前缀等开头的列的列表.但是我不知道如何遍历列名.
I'd like to apply a function to each row, but only from col_00
to col_51
and to cd_00
to cd_90
separately. To do this, I thought I'd collect the column names into a list, fe. to_work_with
would be the list of columns starting with the prefix 'col', apply the function to df[to_work_with]
. Then I'd change the to_work_with
and it would contain the list of columns starting with the 'cd' prefix et cetera. But I don't know how to iterate through the column names.
基本上,我要寻找的是此功能:
So basically, the thing I'm looking for is this function:
to_work_with = column names in the df that start with "thisstring"
我该怎么做?谢谢!
推荐答案
您可以使用 boolean indexing
与
You can use boolean indexing
with str.startswith
:
cols = df.columns[df.columns.str.startswith('cd')]
print (cols)
Index(['cd_00', 'cd_01', 'cd_02', 'cd_90'], dtype='object')
示例:
print (df)
col_00 col_01 col_02 col_51 bc_00 cd_00 cd_01 cd_02 cd_90
0 1 2 3 4 5 6 7 8 9
cols = df.columns[df.columns.str.startswith('cd')]
print (cols)
Index(['cd_00', 'cd_01', 'cd_02', 'cd_90'], dtype='object')
#if want apply some function for filtered columns only
def f(x):
return x + 1
df[cols] = df[cols].apply(f)
print (df)
col_00 col_01 col_02 col_51 bc_00 cd_00 cd_01 cd_02 cd_90
0 1 2 3 4 5 7 8 9 10
使用list comprehension
的另一种解决方案:
Another solution with list comprehension
:
cols = [col for col in df.columns if col.startswith("cd")]
print (cols)
['cd_00', 'cd_01', 'cd_02', 'cd_90']
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