JSON to Pandas DataFrame Converter

About JSON to Pandas DataFrame Converter

Convert JSON data to Python pandas DataFrame code. Perfect for data analysis, machine learning projects, and scientific computing with Python.

Key Features

• Python Code Generation: Generates ready-to-run Python code
• Import Styles: Choose between standard and direct import statements
• Custom Variable Names: Specify your preferred DataFrame variable name
• Multiple Formats: Supports arrays of objects, single objects, and primitive values
• Column-Oriented Data: Automatically detects column-oriented JSON structures
• Proper Escaping: Handles special characters in strings correctly
• Display Code: Includes code to display DataFrame info and shape
• File Upload: Upload JSON files directly or paste data

How to Use

1. Input JSON Data: Paste your JSON data or upload a .json file
2. Configure Options: Choose import style, variable name, and other settings
3. Review Output: The Python code updates automatically
4. Copy or Download: Use the Copy or Download button to save your code
5. Run in Python: Execute the code in your Python environment

Example Conversion

JSON Input:

[
  {"name": "John Doe", "age": 28, "city": "New York"},
  {"name": "Jane Smith", "age": 34, "city": "London"}
]

Python Output:

import pandas as pd

# Create DataFrame from list of dictionaries
data = [
    {'name': 'John Doe', 'age': 28, 'city': 'New York'},
    {'name': 'Jane Smith', 'age': 34, 'city': 'London'}
]
df = pd.DataFrame(data)

# Display DataFrame
print(df)

# Display DataFrame info
print(f"\nShape: {df.shape}")
print(f"Columns: {list(df.columns)}")

Data Structure Support

• List of Dictionaries: Most common format, creates DataFrame with columns from keys
• Column-Oriented Dict: Dictionary with arrays as values (each key is a column)
• Single Dictionary: Creates single-row DataFrame
• List of Primitives: Creates single-column DataFrame named 'value'
• Single Value: Creates single-cell DataFrame

Common Use Cases

• Data Analysis: Convert JSON API responses to pandas DataFrames
• Machine Learning: Prepare JSON data for ML model training
• Data Science: Transform JSON datasets for statistical analysis
• ETL Pipelines: Generate code for data transformation workflows
• Jupyter Notebooks: Quick DataFrame creation in notebooks
• Data Exploration: Convert JSON to DataFrame for exploratory data analysis

Pandas DataFrame Benefits

• Powerful Operations: Filter, group, aggregate, and transform data easily
• Data Cleaning: Handle missing values, duplicates, and data types
• Visualization: Create plots and charts with matplotlib/seaborn
• Integration: Works seamlessly with NumPy, scikit-learn, and other libraries
• Performance: Optimized for large datasets with vectorized operations

Requirements

To run the generated code, you need Python with pandas installed:

pip install pandas

Privacy & Security

All conversions happen locally in your browser. Your JSON data is never uploaded to any server, ensuring complete privacy and security.