Python Dictionary with Multiple Values to DataFrame
Last Updated :
28 Apr, 2025
Python's powerful libraries like Pandas make data manipulation and analysis easier. One of the most common things that can be performed with Pandas is to convert data structures like Dictionaries into Dataframes. In this article, we are covering how to convert Python dictionaries with multiple values into DataFrames.
Convert Python Dictionary with Multiple Values to DataFrame
Below are some ways by which we can convert a Python Dictionary with Multiple Values to a DataFrame in Python:
- Using pd.DataFrame()
- Using pd.DataFrame.from_dict()
- Using pd.DataFrame.from_records()
- Using pd.DataFrame.from_dict with orient
Convert Dictionary to DataFrame Using pd.DataFrame()
In this example, a Pandas DataFrame, `df`, is directly created from a nested dictionary using pd.DataFrame(data), where each outer key represents a column, inner keys serve as row indices, and corresponding values fill the table. The resulting DataFrame displays tabular data with students as rows and attributes as columns.
Python3
import pandas as pd
data = {
"Shravan": {"Enrollment No.": 225, "Branch": "CSE", "CGPA": 7.5},
"Jitu": {"Enrollment No.": 250, "Branch": "CSE", "CGPA": 7.0},
"Ram": {"Enrollment No.": 249, "Branch": "CSE", "CGPA": 9.1},
}
# Using pd.DataFrame directly
df = pd.DataFrame(data)
# Print the DataFrame
print(df)
Output:
Shravan Jitu Ram
Enrollment No. 225 250 249
Branch CSE CSE CSE
CGPA 7.5 7.0 9.1
Python Convert Dictionary to DataFrame Using pd.DataFrame.from_dict()
In this example, a Pandas DataFrame is created from a nested dictionary using pd.DataFrame.from_dict() where each outer key represents a student's name and inner keys correspond to enrollment number, branch, and CGPA. The resulting DataFrame, `df`, displays this tabular data with students as rows and attributes as columns.
Python3
import pandas as pd
data = {
"Shravan": {"Enrollment No.": 225, "Branch": "CSE", "CGPA": 7.5},
"Jitu": {"Enrollment No.": 250, "Branch": "CSE", "CGPA": 7.0},
"Ram": {"Enrollment No.": 249, "Branch": "CSE", "CGPA": 9.1},
}
df = pd.DataFrame.from_dict(data)
print(df)
Output:
Shravan Jitu Ram
Enrollment No. 225 250 249
Branch CSE CSE CSE
CGPA 7.5 7.0 9.1
Python Dictionary to Pandas DataFrame Using pd.DataFrame.from_records()
In this example, a Pandas DataFrame, `df_method3`, is created using pd.DataFrame.from_records() with a list of key-value pairs extracted from the nested dictionary. The resulting DataFrame displays tabular data with students as rows and attributes as columns.
Python3
import pandas as pd
data = {
"Shravan": {"Enrollment No.": 225, "Branch": "CSE", "CGPA": 7.5},
"Jitu": {"Enrollment No.": 250, "Branch": "CSE", "CGPA": 7.0},
"Ram": {"Enrollment No.": 249, "Branch": "CSE", "CGPA": 9.1},
}
# Using pd.DataFrame.from_records
df_method3 = pd.DataFrame.from_records(list(data.items()))
# Print the DataFrame
print(df_method3)
Output:
0 1
0 Shravan {'Enrollment No.': 225, 'Branch': 'CSE', 'CGPA...
1 Jitu {'Enrollment No.': 250, 'Branch': 'CSE', 'CGPA...
2 Ram {'Enrollment No.': 249, 'Branch': 'CSE', 'CGPA...
Python Dict into DataFrame Using orient Parameter
In this example, two Pandas DataFrames are created from the nested dictionary 'data' using the pd.DataFrame.from_dict()
method with different orientation settings
Python3
import pandas as pd
data = {
"Shravan": {"Enrollment No.": 225, "Branch": "CSE", "CGPA": 7.5},
"Jitu": {"Enrollment No.": 250, "Branch": "CSE", "CGPA": 7.0},
"Ram": {"Enrollment No.": 249, "Branch": "CSE", "CGPA": 9.1},
}
print("DataFrame with columns as index and rows as values (orient='index')")
df_index = pd.DataFrame.from_dict(data, orient='index')
print(df_index)
print("\nDataFrame with values as columns and names as rows (orient='columns')")
df_columns = pd.DataFrame.from_dict(data, orient='columns')
print(df_columns)
Output:
DataFrame with columns as index and rows as values (orient='index')
Enrollment No. Branch CGPA
Shravan 225 CSE 7.5
Jitu 250 CSE 7.0
Ram 249 CSE 9.1
DataFrame with values as columns and names as rows (orient='columns')
Shravan Jitu Ram
Enrollment No. 225 250 249
Branch CSE CSE CSE
CGPA 7.5 7.0 9.1
Similar Reads
Python Tutorial | Learn Python Programming Language Python Tutorial â Python is one of the most popular programming languages. Itâs simple to use, packed with features and supported by a wide range of libraries and frameworks. Its clean syntax makes it beginner-friendly.Python is:A high-level language, used in web development, data science, automatio
10 min read
Python Interview Questions and Answers Python is the most used language in top companies such as Intel, IBM, NASA, Pixar, Netflix, Facebook, JP Morgan Chase, Spotify and many more because of its simplicity and powerful libraries. To crack their Online Assessment and Interview Rounds as a Python developer, we need to master important Pyth
15+ min read
Non-linear Components In electrical circuits, Non-linear Components are electronic devices that need an external power source to operate actively. Non-Linear Components are those that are changed with respect to the voltage and current. Elements that do not follow ohm's law are called Non-linear Components. Non-linear Co
11 min read
Python OOPs Concepts Object Oriented Programming is a fundamental concept in Python, empowering developers to build modular, maintainable, and scalable applications. By understanding the core OOP principles (classes, objects, inheritance, encapsulation, polymorphism, and abstraction), programmers can leverage the full p
11 min read
Python Projects - Beginner to Advanced Python is one of the most popular programming languages due to its simplicity, versatility, and supportive community. Whether youâre a beginner eager to learn the basics or an experienced programmer looking to challenge your skills, there are countless Python projects to help you grow.Hereâs a list
10 min read
Python Exercise with Practice Questions and Solutions Python Exercise for Beginner: Practice makes perfect in everything, and this is especially true when learning Python. If you're a beginner, regularly practicing Python exercises will build your confidence and sharpen your skills. To help you improve, try these Python exercises with solutions to test
9 min read
Python Programs Practice with Python program examples is always a good choice to scale up your logical understanding and programming skills and this article will provide you with the best sets of Python code examples.The below Python section contains a wide collection of Python programming examples. These Python co
11 min read
Spring Boot Tutorial Spring Boot is a Java framework that makes it easier to create and run Java applications. It simplifies the configuration and setup process, allowing developers to focus more on writing code for their applications. This Spring Boot Tutorial is a comprehensive guide that covers both basic and advance
10 min read
Class Diagram | Unified Modeling Language (UML) A UML class diagram is a visual tool that represents the structure of a system by showing its classes, attributes, methods, and the relationships between them. It helps everyone involved in a projectâlike developers and designersâunderstand how the system is organized and how its components interact
12 min read
Enumerate() in Python enumerate() function adds a counter to each item in a list or other iterable. It turns the iterable into something we can loop through, where each item comes with its number (starting from 0 by default). We can also turn it into a list of (number, item) pairs using list().Let's look at a simple exam
3 min read