sort dataframe by column
df.sort_values(by='col1', ascending=False)sort dataframe by column
df.sort_values(by='col1', ascending=False)pandas sort columns by name
df = df.reindex(sorted(df.columns), axis=1)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)dataframe sort by column
sorted = df.sort_values('column-to-sort-on', ascending=False)
#or
df.sort_values('name', inplace=True)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']Copyright © 2021 Codeinu
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