如何从数据透视表中删除列名/标签，而剩余的列名下降到索引名级别？

Question

I have a pivot table using CategoricalDtype so I can get the month names in order. How can I can drop the column name/label "Month" and then move the month abbreviation names to the same level as "Year"?

... .pivot_table(index='Year',columns='Month',values='UpClose',aggfunc=np.sum))

Current output:

Month   Jan   Feb   Mar  Apr  May   Jun   Jul   Aug   Sep   Oct   Nov  Dec  Total
Year    
1997    12.0  8.0   8.0  12.0  11.0 12.0  14.0  10.0  10.0  10.0  10.0 9.0  126.0
1998    10.0  12.0  14.0 12.0  9.0  11.0  10.0  8.0   11.0  10.0  10.0 12.0 129.0

Desired output:

Year    Jan   Feb   Mar  Apr  May   Jun   Jul   Aug   Sep   Oct   Nov  Dec  Total
1997    12.0  8.0   8.0  12.0  11.0 12.0  14.0  10.0  10.0  10.0  10.0 9.0  126.0
1998    10.0  12.0  14.0 12.0  9.0  11.0  10.0  8.0   11.0  10.0  10.0 12.0 129.0

If I use, data.columns.name = None it will remove the "Month" label, but it doesn't drop the month abbreviations to the same level as "Year.

Answer 1

You need to replace the column name by doing something like this Renaming columns in dataframe wrt another specific column

# replace the Month with year 
df = df.rename(columns={"Month":"Year"})

# drop first column
df = df.iloc[1:].reset_index(drop=True)