sort dataframe by column
df.sort_values(by='col1', ascending=False)
sort dataframe by column
df.sort_values(by='col1', ascending=False)
df sort values
>>> 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
sort a dataframe by a column valuepython
>>> df.sort_values(by=['col1'])
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
dataframe, sort by columns
final_df = df.sort_values(by=['2'], ascending=False)
sort df by column
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)
sort dataframe by column
df.sort_values(by='col1', ascending=False, na_position='first', inplace=True)
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