PYTHON

pandas sort columns by name

df = df.reindex(sorted(df.columns), axis=1)

dataframe sort by column

sorted = df.sort_values('column-to-sort-on', ascending=False)
#or
df.sort_values('name', inplace=True) 

dataframe, sort by columns

final_df = df.sort_values(by=['2'], ascending=False)

pandas reorder columns by name

#old df columns
df.columns
Index(['A', 'B', 'C', 'D'],dtype='***')
#new column format that we want to rearange
new_col = ['D','C','B','A'] #list of column name in order that we want

df = df[new_col]
df.columns
Index(['D', 'C', 'B', 'A'],dtype='***')
#new column order

pandas sort by columns

# Python, Pandas
# Sorting dataframe

# sort by one column
df.sort_values(by=['col1']) 

# sort by more columns
df.sort_values(by=['col1', 'col2'])

# defaut values
# DataFrame.sort_values(by, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last', ignore_index=False, key=None)

sort columns dataframe

df = df.reindex(sorted(df.columns), axis=1)

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']

pandas head sort by colun name

DataFrame.sort_values(
  ['column_to_sort_by'], 
  axis=0, 
  ascending=True, 
  inplace=False, 
  kind='quicksort', 
  na_position='last', 
  ignore_index=False, 
  key=None
)

pandas dataframe sort by column

df.sort_values(by=['col1])

df sort by column names

df.sort_index(axis=1)

python dataframe sort by column name

>>> result = df.sort(['A', 'B'], ascending=[1, 0])