pandas 将列表追加到列名称列表中

问题描述

我正在寻找一种将列名列表附加到pandas中的DataFrame中现有列名的方式，然后按col_start + col_add对其重新排序.

DataFrame已经包含来自col_start的列.

类似的东西:

import pandas as pd

df = pd.read_csv(file.csv)

col_start = ["col_a", "col_b", "col_c"]
col_add = ["Col_d", "Col_e", "Col_f"]
df = pd.concat([df,pd.DataFrame(columns = list(col_add))]) #Add columns
df = df[[col_start.extend(col_add)]] #Rearrange columns

还有，是否有一种方法可以将col_start中每个项目的首字母大写，类似于title()或capitalize()?

解决方案

您的代码就快要存在了，有几件事:

df = pd.concat([df,pd.DataFrame(columns = list(col_add))])

可以简化为这样，因为col_add已经是一个列表:

df = pd.concat([df,pd.DataFrame(columns = col_add)])

此外，您也可以将2个列表加在一起，这样:

df = df[[col_start.extend(col_add)]]

成为

df = df[col_start+col_add]

要大写列表中的第一个字母，只需执行以下操作:

In [184]:
col_start = ["col_a", "col_b", "col_c"]
col_start = [x.title() for x in col_start]
col_start

Out[184]:
['Col_A', 'Col_B', 'Col_C']

编辑

为避免大写的列名上出现KeyError，您需要在调用concat之后大写，这些列具有向量化的str title方法:

In [187]:
df = pd.DataFrame(columns = col_start + col_add)
df

Out[187]:
Empty DataFrame
Columns: [col_a, col_b, col_c, Col_d, Col_e, Col_f]
Index: []

In [188]:
df.columns = df.columns.str.title()
df.columns

Out[188]:
Index(['Col_A', 'Col_B', 'Col_C', 'Col_D', 'Col_E', 'Col_F'], dtype='object')

I'm looking for a way to append a list of column names to existing column names in a DataFrame in pandas and then reorder them by col_start + col_add.

The DataFrame already contains the columns from col_start.

Something like:

import pandas as pd

df = pd.read_csv(file.csv)

col_start = ["col_a", "col_b", "col_c"]
col_add = ["Col_d", "Col_e", "Col_f"]
df = pd.concat([df,pd.DataFrame(columns = list(col_add))]) #Add columns
df = df[[col_start.extend(col_add)]] #Rearrange columns

Also, is there a way to capitalize the first letter for each item in col_start, analogous to title() or capitalize()?

解决方案

Your code is nearly there, a couple things:

df = pd.concat([df,pd.DataFrame(columns = list(col_add))])

can be simplified to just this as col_add is already a list:

df = pd.concat([df,pd.DataFrame(columns = col_add)])

Also you can also just add 2 lists together so:

df = df[[col_start.extend(col_add)]]

becomes

df = df[col_start+col_add]

And to capitalise the first letter in your list just do:

In [184]:
col_start = ["col_a", "col_b", "col_c"]
col_start = [x.title() for x in col_start]
col_start

Out[184]:
['Col_A', 'Col_B', 'Col_C']

EDIT

To avoid the KeyError on the capitalised column names, you need to capitalise after calling concat, the columns have a vectorised str title method:

In [187]:
df = pd.DataFrame(columns = col_start + col_add)
df

Out[187]:
Empty DataFrame
Columns: [col_a, col_b, col_c, Col_d, Col_e, Col_f]
Index: []

In [188]:
df.columns = df.columns.str.title()
df.columns

Out[188]:
Index(['Col_A', 'Col_B', 'Col_C', 'Col_D', 'Col_E', 'Col_F'], dtype='object')

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