>>> df.sort_values(by=['col1'], ascending = False)
col1 col2 col3
0 A 2 0
1 A 1 1
2 B 9 9
5 C 4 3
4 D 7 2
3 NaN 8 4
>>> df.sort_values(by='col1', ascending=False)
col1 col2 col3 col4
4 D 7 2 e
5 C 4 3 F
2 B 9 9 c
0 A 2 0 a
1 A 1 1 B
3 NaN 8 4 D
DataFrame.sort_values(self, by, axis=0, ascending=True,
inplace=False, kind='quicksort',
na_position='last',
ignore_index=False)
# Example
df.sort_values(by=['ColToSortBy'])df.rename(columns={1:'month'},inplace=True)
df['month'] = pd.Categorical(df['month'],categories=['December','November','October','September','August','July','June','May','April','March','February','January'],ordered=True)
df = df.sort_values('month',ascending=False)df.sort_values(by=['col1', 'col2'])df = df.reindex(sorted(df.columns), axis=1)