如何让pandas dataframe列标题全部小写?

时间:2021-10-25 08:01:06

I want to make all column headers in my pandas data frame lower case

我想让我的pandas数据框中的所有列标题都小写

Example

If I have:

如果我有:

data =

  country country isocode  year     XRAT          tcgdp
0  Canada             CAN  2001  1.54876   924909.44207
1  Canada             CAN  2002  1.56932   957299.91586
2  Canada             CAN  2003  1.40105  1016902.00180
....

I would like to change XRAT to xrat by doing something like:

我想通过做类似的事情将XRAT改为xrat:

data.headers.lowercase()

So that I get:

所以我得到:

  country country isocode  year     xrat          tcgdp
0  Canada             CAN  2001  1.54876   924909.44207
1  Canada             CAN  2002  1.56932   957299.91586
2  Canada             CAN  2003  1.40105  1016902.00180
3  Canada             CAN  2004  1.30102  1096000.35500
....

I will not know the names of each column header ahead of time.

我不会提前知道每个列标题的名称。

3 个解决方案

#1


76  

You can do it like this:

你可以这样做:

data.columns = map(str.lower, data.columns)

or

要么

data.columns = [x.lower() for x in data.columns]

example:

例:

>>> data = pd.DataFrame({'A':range(3), 'B':range(3,0,-1), 'C':list('abc')})
>>> data
   A  B  C
0  0  3  a
1  1  2  b
2  2  1  c
>>> data.columns = map(str.lower, data.columns)
>>> data
   a  b  c
0  0  3  a
1  1  2  b
2  2  1  c

#2


40  

You could do it easily with str.lower for columns:

您可以使用str.lower轻松完成列的操作:

df.columns = df.columns.str.lower()

Example:

例:

In [63]: df
Out[63]: 
  country country isocode  year     XRAT         tcgdp
0  Canada             CAN  2001  1.54876  9.249094e+05
1  Canada             CAN  2002  1.56932  9.572999e+05
2  Canada             CAN  2003  1.40105  1.016902e+06

In [64]: df.columns = df.columns.str.lower()

In [65]: df
Out[65]: 
  country country isocode  year     xrat         tcgdp
0  Canada             CAN  2001  1.54876  9.249094e+05
1  Canada             CAN  2002  1.56932  9.572999e+05
2  Canada             CAN  2003  1.40105  1.016902e+06

#3


10  

If you want to do the rename using a chained method call, you can use

如果要使用链式方法调用进行重命名,则可以使用

data.rename(
    columns=unicode.lower
)

(Python 2)

(Python 2)

or

要么

data.rename(
    columns=str.lower
)

(Python 3)

(Python 3)

#1


76  

You can do it like this:

你可以这样做:

data.columns = map(str.lower, data.columns)

or

要么

data.columns = [x.lower() for x in data.columns]

example:

例:

>>> data = pd.DataFrame({'A':range(3), 'B':range(3,0,-1), 'C':list('abc')})
>>> data
   A  B  C
0  0  3  a
1  1  2  b
2  2  1  c
>>> data.columns = map(str.lower, data.columns)
>>> data
   a  b  c
0  0  3  a
1  1  2  b
2  2  1  c

#2


40  

You could do it easily with str.lower for columns:

您可以使用str.lower轻松完成列的操作:

df.columns = df.columns.str.lower()

Example:

例:

In [63]: df
Out[63]: 
  country country isocode  year     XRAT         tcgdp
0  Canada             CAN  2001  1.54876  9.249094e+05
1  Canada             CAN  2002  1.56932  9.572999e+05
2  Canada             CAN  2003  1.40105  1.016902e+06

In [64]: df.columns = df.columns.str.lower()

In [65]: df
Out[65]: 
  country country isocode  year     xrat         tcgdp
0  Canada             CAN  2001  1.54876  9.249094e+05
1  Canada             CAN  2002  1.56932  9.572999e+05
2  Canada             CAN  2003  1.40105  1.016902e+06

#3


10  

If you want to do the rename using a chained method call, you can use

如果要使用链式方法调用进行重命名,则可以使用

data.rename(
    columns=unicode.lower
)

(Python 2)

(Python 2)

or

要么

data.rename(
    columns=str.lower
)

(Python 3)

(Python 3)