How to create DataFrame from dictionary in Python-Pandas?

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.

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:

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:

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:

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:

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:

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: