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How to create DataFrame from dictionary in Python-Pandas?

  • Last Updated : 10 Jul, 2020

Let’s discuss how to create DataFrame from dictionary in Pandas. There are multiple ways to do this task.

Method 1: Create DataFrame from Dictionary using default Constructor of pandas.Dataframe class.

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Code:






# import pandas library
import pandas as pd
  
# dictionary with list object in values
details = {
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'],
    'Age' : [23, 21, 22, 21],
    'University' : ['BHU', 'JNU', 'DU', 'BHU'],
}
  
# creating a Dataframe object 
df = pd.DataFrame(details)
  
df

Output:

pandas-create-dataframe-1

Method 2: Create DataFrame from Dictionary with user-defined indexes.

Code:




# import pandas library
import pandas as pd
  
# dictionary with list object in values
details = {
    'Name' : ['Ankit', 'Aishwarya', 'Shaurya', 'Shivangi'],
    'Age' : [23, 21, 22, 21],
    'University' : ['BHU', 'JNU', 'DU', 'BHU'],
}
  
# creating a Dataframe object from dictionary 
# with custom indexing
df = pd.DataFrame(details, index = ['a', 'b', 'c', 'd'])
  
df

Output:

pandas-create-dataframe-2

Method 3: Create DataFrame from simple dictionary i.e dictionary with key and simple value like integer or string value.

Code:






# import pandas library
import pandas as pd
  
# dictionary
details = {
    'Ankit' : 22,
    'Golu' : 21,
    'hacker' : 23
    }
  
# creating a Dataframe object from a list 
# of tuples of key, value pair
df = pd.DataFrame(list(details.items()))
  
df

Output:

pandas-create-dataframe-3

Method 4: Create DataFrame from Dictionary with required columns only.

Code:




# import pandas library
import pandas as pd
  
# dictionary with list object in values
details = {
    '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:

pandas-create-dataframe-4

Method 5: Create DataFrame from Dictionary with different Orientation i.e. Dictionary key is act as indexes in Dataframe.

Code:




# import pandas library
import pandas as pd
  
# dictionary with list object in values
details = {
    '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:

pandas-create-dataframe-5

Method 6: Create DataFrame from nested Dictionary.

Code:




# import pandas library
import pandas as pd
  
# dictionary with dictionary object
# in values i.e. nested dictionary
details =
    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 indexes
df = df.transpose()
  
df

Output:

pandas-create-dataframe-6




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