Creating a Pandas DataFrame using Dict of Tuples in Python

Working with Python dictionaries containing tuples is a common scenario, especially when dealing with heterogeneous data. Transforming this data into a Pandas DataFrame allows for efficient manipulation and analysis. In this article, we will see how we can convert a dictionary with a tuple into a DataFrame in Python.

Convert Dictionary with Tuple into a DataFrame in Python

Below are the different ways by which we can convert dictionary with tuple into a DataFrame in Python:

• Using pandas.DataFrame.from_dict()
• Using pandas.DataFrame()
• Using List Comprehension

Using pandas.DataFrame.from_dict() Method

In this example, a Python dictionary data with keys ‘A’ and ‘B’, each containing a list of tuples, is converted into a DataFrame using the from_dict() method from the Pandas library. The resulting Pandas DataFrame df is then printed, creating a tabular representation of the nested tuples.

Python3

import pandas as pd

# Sample dictionary
data = {'A': [(1, 'x'), (2, 'y'), (3, 'z')],
        'B': [(4, 'p'), (5, 'q'), (6, 'r')]}

# Convert dictionary to DataFrame
df = pd.DataFrame.from_dict(data, orient='index').transpose()

print(df)

Output:

        A       B
0  (1, x)  (4, p)
1  (2, y)  (5, q)
2  (3, z)  (6, r)

Using pandas.DataFrame() Method

In this example, a Python dictionary data with keys ‘A’ and ‘B’, each containing a list of tuples, is directly converted into a DataFrame using the Pandas library. The resulting DataFrame df is then printed, generating a tabular structure where each tuple is expanded into separate columns.

Python3

import pandas as pd

# Sample dictionary
data = {'A': [(1, 'x'), (2, 'y'), (3, 'z')],
        'B': [(4, 'p'), (5, 'q'), (6, 'r')]}

# Convert dictionary to DataFrame
df = pd.DataFrame(data)

print(df)

Output:

        A       B
0  (1, x)  (4, p)
1  (2, y)  (5, q)
2  (3, z)  (6, r)

Using List Comprehension

In this example, the original Python dictionary data_dict with keys ‘Key1’, ‘Key2’, and ‘Key3’, each containing a tuple, is converted into a DataFrame using list comprehension and the Pandas library. The resulting DataFrame df is then printed, showcasing a tabular structure where each tuple’s elements are expanded into separate columns (‘Column1’ and ‘Column2’) with the dictionary keys as the index.

Python3

import pandas as pd

# Original dictionary with tuples
data_dict = {'Key1': ('A', 10), 'Key2': ('B', 20), 'Key3': ('C', 30)}

# Creating a DataFrame using list comprehension
df = pd.DataFrame([(key,) + values for key, values in data_dict.items()],
                  columns=['Index', 'Column1', 'Column2']).set_index('Index')

# Displaying the DataFrame
print(df)

Output:

      Column1  Column2
Index                 
Key1        A       10
Key2        B       20
Key3        C       30