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
how to sort in pandas
// Single sort
>>> df.sort_values(by=['col1'],ascending=False)
// ascending => [False(reverse order) & True(default)]
// Multiple Sort
>>> df.sort_values(by=['col1','col2'],ascending=[True,False])
// with apply()
>>> df[['col1','col2']].apply(sorted,axis=1)
// axis = [1 & 0], 1 = 'columns', 0 = 'index'
dataframe, sort by columns
final_df = df.sort_values(by=['2'], ascending=False)
sort by dataframe
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'])
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)
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