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pandas sort columns by name

df = df.reindex(sorted(df.columns), axis=1)
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dataframe sort by column

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

dataframe, sort by columns

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

Sorting Dataframes by Column Python Pandas

# Sorting Pandas Dataframe in Descending Order
  
# importing pandas library
import pandas as pd
  
# Initializing the nested list with Data set
age_list = [['Afghanistan', 1952, 8425333, 'Asia'],
            ['Australia', 1957, 9712569, 'Oceania'],
            ['Brazil', 1962, 76039390, 'Americas'],
            ['China', 1957, 637408000, 'Asia'],
            ['France', 1957, 44310863, 'Europe'],
            ['India', 1952, 3.72e+08, 'Asia'],
            ['United States', 1957, 171984000, 'Americas']]
  
# creating a pandas dataframe
df = pd.DataFrame(age_list, columns=['Country', 'Year',
                                     'Population', 'Continent'])
  
# Sorting by column "Population"
df.sort_values(by=['Population'], ascending=False)
Comment

sort columns dataframe

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

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']
Comment

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
)
Comment

pandas dataframe sort by column

df.sort_values(by=['col1])
Comment

df sort by column names

df.sort_index(axis=1)
Comment

python dataframe sort by column name

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