pandas 熊猫重命名索引
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Pandas rename index
提问by a1234
I have the following dataframe, where I want to rename the index fromsummaryto id:
我有以下数据框，我想将索引重命名summary为id：
summary student count
0 error 6
1 yes 1
2 no 1
3 other 9
I have tried:
newdf = df.reset_index().rename(columns={df.index.name:'foo'})which gives:
我试过：
newdf = df.reset_index().rename(columns={df.index.name:'foo'})它给出：
summary index student count
0 0 error 6
1 1 yes 1
2 2 no 1
3 3 other 9
I have also tried: df.index.rename('foo', inplace = True)which gives:
我也试过：df.index.rename('foo', inplace = True)它给出：
summary student count
foo
0 error 6
1 yes 1
2 no 1
3 other 9
I have also tried: df.rename_axis('why', inplace = True)which gives:
我也试过：df.rename_axis('why', inplace = True)它给出：
summary student count
why
0 error 6
1 yes 1
2 no 1
3 other 9
When I do df.dtypes:
当我这样做时df.dtypes：
summary
student object
count init64
dtype: object
What I would like:
我想要什么：
id student count
0 error 6
1 yes 1
2 no 1
3 other 9
OR:
或者：
student count
0 error 6
1 yes 1
2 no 1
3 other 9
回答by ALollz
You need to remove the column name:
您需要删除列名：
df.rename_axis(None, axis=1).rename_axis('id', axis=0)
##if pd.__version__ == 0.24.0
#df.rename_axis([None], axis=1).rename_axis('id')
The problem is that 'summary'is your column name. When there is no index name, the column name is placed directly above the index, which can be misleading:
问题是'summary'你的列名。当没有索引名时，列名直接放在索引的上方，这可能会产生误导：
import pandas as pd
df = pd.DataFrame([[1]*2]*4, columns=['A', 'B'])
df.columns.name = 'col_name'
print(df)
#col_name A B
#0 1 1
#1 1 1
#2 1 1
#3 1 1
When you then try to add an index name, it becomes clear that 'col_name'was really the column name.
当您然后尝试添加索引名称时，很明显这'col_name'确实是列名称。
df.index.name = 'idx_name'
print(df)
#col_name A B
#idx_name
#0 1 1
#1 1 1
#2 1 1
#3 1 1
There is no ambiguity though: when you have an index name, the columns are raised one level, which allows you to distinguish between an index name and a column name.
但是没有歧义：当您有索引名称时，列会升高一级，这样您就可以区分索引名称和列名称。
df = pd.DataFrame([[1]*2]*4, columns=['A', 'B'])
df.index.name = 'idx_name'
print(df)
# A B
#idx_name
#0 1 1
#1 1 1
#2 1 1
#3 1 1
回答by Yuca
you need to access the index's properties
您需要访问索引的属性
df.index.name = 'id'
original
原来的
student count
summary
0 error 6
1 yes 1
2 no 1
3 other 9
fixed df:
固定 df：
student count
id
0 error 6
1 yes 1
2 no 1
3 other 9
Update: seems like you had a name for the column's index. You should remove it with
更新：似乎您有列索引的名称。你应该删除它
df.columns.names = ''
df.columns.names = ''
回答by Mohit Musaddi
First you can drop the column:
首先，您可以删除该列：
df = df.drop('summary', axis=1)
df['id'] = np.arange(df.shape[0])
df.set_index('id', inplace=True)
Then you can get the desired result.
然后就可以得到想要的结果了。
