Python 重命名Pandas数据框的一列并将其更改为'；s型

有没有办法将R中变量的名称更改为标签值

例如，当变量表示“年龄段”时，我试图将其更改为“三向分带年龄组”：

我试过这个，但似乎不起作用：

import pandas as pd

Data_2017_18['Three-way banded age group'] = Data_2017_18['ageband'].astype("category")

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注意：将列名重命名为包含空格的名称被认为是一种不好的做法，应该使用下划线来避免

要重命名pandas中的列，只需使用以下方法

import pandas as pd

d = {'ageband': [1, 2], 'col2': [3, 4]}
df = pd.DataFrame(data=d)

# Before :    ageband  col2
# 0        1     3
# 1        2     4
print(f'Before : {df}')

# Rename column name
df=df.rename(columns={'ageband' : "Three-way banded age group"})

# Convert type name to `category`
df[['Three-way banded age group']] = df[['Three-way banded age group']].astype('category')

# After :    Three-way banded age group  col2
# 0                           1     3
# 1                           2     4
print(f'After : {df}')

import pandas as pd

d = {'ageband': [1, 2], 'col2': [3, 4]}
df = pd.DataFrame(data=d)

# Before :    ageband  col2
# 0        1     3
# 1        2     4
print(f'Before : {df}')

# Rename column name
df=df.rename(columns={'ageband' : "Three-way banded age group"})

# Convert type name to `category`
df[['Three-way banded age group']] = df[['Three-way banded age group']].astype('category')

# After :    Three-way banded age group  col2
# 0                           1     3
# 1                           2     4
print(f'After : {df}')