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 columns dataframe
df = df.reindex(sorted(df.columns), axis=1)
python df pandas sort by column
>>> df.sort_values("city08")
city08 cylinders fuelType ... mpgData trany year
99 9 8 Premium ... N Automatic 4-spd 1993
1 9 12 Regular ... N Manual 5-spd 1985
80 9 8 Regular ... N Automatic 3-spd 1985
47 9 8 Regular ... N Automatic 3-spd 1985
3 10 8 Regular ... N Automatic 3-spd 1985
.. ... ... ... ... ... ... ...
9 23 4 Regular ... Y Automatic 4-spd 1993
8 23 4 Regular ... Y Manual 5-spd 1993
7 23 4 Regular ... Y Automatic 3-spd 1993
76 23 4 Regular ... Y Manual 5-spd 1993
2 23 4 Regular ... Y Manual 5-spd 1985
[100 rows x 10 columns]
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