# Python, Pandas# Sorting dataframe df on the values of a column col1# Return sorted array without modifying the original one
df.sort_values(by=["col1"])# Sort the original array permanently
df.sort_values(by=["col1"], inplace =True)
# Sorting Pandas Dataframe in Descending Order# importing pandas libraryimport 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)
# 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']