Let’s discuss how to create DataFrame from dictionary in Pandas. There are multiple ways to do this task.
Create DataFrame from Dictionary using default Constructor of pandas.Dataframe class
Python3
# import pandas libraryimport pandas as pd# dictionary with list object in valuesdetails = { 'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'], 'Age' : [23, 21, 22, 21], 'University' : ['BHU', 'JNU', 'DU', 'BHU'],}# creating a Dataframe objectdf = pd.DataFrame(details)df |
Output:
Create DataFrame from Dictionary with user-defined indexes.
Python3
# import pandas libraryimport pandas as pd# dictionary with list object in valuesdetails = { 'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'], 'Age' : [23, 21, 22, 21], 'University' : ['BHU', 'JNU', 'DU', 'BHU'],}# creating a Dataframe object from dictionary# with custom indexingdf = pd.DataFrame(details, index = ['a', 'b', 'c', 'd'])df |
Output:
Create DataFrame from simple dictionary i.e dictionary with key and simple value like integer or string value
Python3
# import pandas libraryimport pandas as pd# dictionarydetails = { 'Ankit' : 22, 'Golu' : 21, 'hacker' : 23 }# creating a Dataframe object from a list# of tuples of key, value pairdf = pd.DataFrame(list(details.items()))df |
Output:
Create DataFrame from Dictionary with required columns only
Python3
# import pandas libraryimport pandas as pd# dictionary with list object in valuesdetails = { 'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'], 'Age' : [23, 21, 22, 21], 'University' : ['BHU', 'JNU', 'DU', 'BHU'],}# creating a Dataframe object with skipping# one column i.e skipping age column.df = pd.DataFrame(details, columns = ['Name', 'University'])df |
Output:
Create DataFrame from Dictionary with different Orientation i.e. Dictionary key is act as indexes in Dataframe
Python3
# import pandas libraryimport pandas as pd# dictionary with list object in valuesdetails = { 'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'], 'Age' : [23, 21, 22, 21], 'University' : ['BHU', 'JNU', 'DU', 'BHU'],}# creating a Dataframe object in which dictionary# key is act as index value and column value is# 0, 1, 2...df = pd.DataFrame.from_dict(details, orient = 'index')df |
Output:
Create DataFrame from nested Dictionary
Python3
# import pandas libraryimport pandas as pd# dictionary with dictionary object# in values i.e. nested dictionarydetails = { 0 : { 'Name' : 'Ankit', 'Age' : 22, 'University' : 'BHU' }, 1 : { 'Name' : 'Aishwarya', 'Age' : 21, 'University' : 'JNU' }, 2 : { 'Name' : 'Shaurya', 'Age' : 23, 'University' : 'DU' }}# creating a Dataframe object# from nested dictionary# in which inside dictionary# key is act as index value# and column value is 0, 1, 2...df = pd.DataFrame(details)# swap the columns with indexesdf = df.transpose()df |
Output:
