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)