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BudiBadu
Online Pandas Compiler
Pandas is Python's premier library for data analysis and manipulation, used by millions of data professionals worldwide. Our dedicated online Pandas compiler provides a complete browser-based environment for working with structured data using powerful DataFrame and Series objects. Built on top of NumPy, Pandas offers high-performance, easy-to-use data structures perfect for real-world data analysis, making it the industry standard for data manipulation in Python. From financial analysis to scientific research, Pandas is the tool of choice for professionals who need to clean, transform, and analyze data efficiently.
This compiler includes Pandas 2.x with NumPy, enabling you to perform complex data operations instantly through Pyodide WebAssembly technology. You can work with DataFrames (two-dimensional labeled data structures with columns of potentially different types) and Series (one-dimensional labeled arrays), performing operations like data cleaning, transformation, statistical analysis, and time series manipulation. The platform provides all the tools you need for comprehensive data analysis including powerful indexing and slicing capabilities, GroupBy operations for split-apply-combine functionality, sophisticated missing data handling, and SQL-like operations for combining multiple datasets. You can also upload and use files or folders directly in your code for data processing and analysis workflows. This compiler is online and completely free to use.
Our comprehensive example collection covers essential data manipulation techniques including DataFrame basics, data selection and filtering, grouping data by categories with aggregate functions, detecting and filling missing values, and combining datasets using merge, join, and concatenate operations. You'll also learn time series analysis with datetime data, resampling techniques, and rolling window calculations. The examples demonstrate data import/export with various file formats (CSV, JSON) and advanced data transformation pipelines that are commonly used in production environments.
Who Should Use This
- Data analysts working with structured datasets and creating insights
- Data scientists preprocessing data for machine learning models
- Business intelligence professionals building reports and dashboards
- Financial analysts performing portfolio management and risk analysis
- ETL developers building data pipelines and transformation workflows
- Students learning data analysis and manipulation techniques with Python
Part of the BudiBadu Ecosystem
Specialized Online Python compiler powered by Pyodide WebAssembly. Run Python Library directly in your browser with zero setup.
Pyodide
WebAssembly
Monaco Editor
Python 3.13