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 4df 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 4dataframe sort values descending
df.sort_values(by='field_name',ascending=False)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 4df.sort_values(by='col1',asending=True)
>>> 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 Dhow 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'pandas value_counts sort descending
df1 = df.groupby('Category')['Name'].value_counts().sort_values(as​cending=False)Copyright © 2021 Codeinu
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