sort dataframe by column
df.sort_values(by='col1', ascending=False)
sort dataframe by column
df.sort_values(by='col1', 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 4
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)
pandas sort dataframe by column
# Basic syntax:
import pandas as pd
df.sort_values(by=['col1'])
# Note, this does not sort in place unless you add inplace=True
# Note, add ascending=False if you want to sort in decreasing order
# Note, to sort by more than one column, add other column names to the
# list like by=['col1', 'col2']
sort columns dataframe
df = df.reindex(sorted(df.columns), axis=1)
python dataframe sort by column name
>>> result = df.sort(['A', 'B'], ascending=[1, 0])
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