1) just replace the index name
df.index = list
2) When adjusting the index, the following items should also be adjusted accordingly:
df.reindex(list)
Note that if an index that is not in df appears in the list , the following items will become nan
Example:
df=pd.DataFrame({'a':[1,2,3],'b':[4,5,6],'c':[7,8,9]},columns=['a','b','c'],index=['11','22','33'])
print(df)：
a b c
11 1 4 7
22 2 5 8
33 3 6 9
df.index = ['44','55','66']
print(df)：
a b c
44 1 4 7
55 2 5 8
66 3 6 9
df=df.reindex(['22','11','44','33'])
print(df)
a b c
22 2 5 8
11 1 4 7
44 NaN NaN NaN
33 3 6 9
3) Replace the columns
df.columns = ['a','b','c'] # Just replace the list with abc, the actual content has not changed
To achieve a reindex-like effect, you need to use df=df[[ 'c' , 'b' , 'a' ]]
4) Notes on index
If the top cell in the first column of excel is empty, the first column will become index after read_excel
If you are reading the sereis in the df , please note that the index will become 1,2,3,4,5... .