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Top 23 Python Panda Projects
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30-Days-Of-Python
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
30-Days-Of-Python
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Sevalla
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Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
https://github.com/pandas-dev/pandas/issues/58062 :
> On disk Parquet appears to store the category data as logical type String which is compressed with snappy and encoded
Arrow Flight RPC handles nested structs with enums over the wire somehow too FWIU
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
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pandas-ai
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
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datasets
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Hugging Face Datasets -- the library that lets you download and manage datasets from the Hugging Face Hub, as well as being a convenient vendor-neutral interface for your own datasets.
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InfluxDB
InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
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Below are the key insights. If you want to see the Python code I used to do this analysis and generate the charts using Seaborn, you can find my full analysis Jupyter notebook on my Github repo here: Tip Analysis.ipynb
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ydata-profiling
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
WhatTheDuck does SQL with duckdb-wasm IIRC
Pygwalker does open-source descriptive statistics and charts from pandas dataframes: https://github.com/Kanaries/pygwalker
ydata-profiling does Exploratory Data Analysis (EDA) with Pandas and Spark DataFrames and integrates with various apps: https://github.com/ydataai/ydata-profiling
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Project mention: Why Pandas feels clunky when coming from R (2024) | news.ycombinator.com | 2025-06-07
pandas* per the style guide (nobody follows it)
also I recommend trying Ibis. created by the creator of pandas originally and solves so many of the issues
https://ibis-project.org
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Project mention: Rivian GeoLocation Plotting with IRIS Cloud Document and Databricks | dev.to | 2024-12-26
We are using geopandas and geodatasets for a straight forward approach to plotting.
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Mimesis
Mimesis is a robust data generator for Python that can produce a wide range of fake data in multiple languages.
View the Project on GitHub
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AWS Data Wrangler
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
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SaaSHub
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NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Python Pandas discussion
Python Pandas related posts
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Pandas AI
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Unlocking Speed: Mastering High-Performance Data Structures for Python Data Science
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DumPy: NumPy except it's OK if you're dum
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Narwhals
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I Don't Like NumPy
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PandaAI: Talk to Your Data, Not to Your Code!
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Show HN: SearchArray – Full text search that feels like a NumPy array
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A note from our sponsor - SaaSHub
www.saashub.com | 1 Sep 2025
Index
What are some of the best open-source Panda projects in Python? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | 30-Days-Of-Python | 48,905 |
| 2 | Pandas | 46,447 |
| 3 | tqdm | 30,339 |
| 4 | data-science-ipython-notebooks | 28,284 |
| 5 | pandas-ai | 21,924 |
| 6 | datasets | 20,575 |
| 7 | yfinance | 18,847 |
| 8 | pygwalker | 15,122 |
| 9 | Dask | 13,444 |
| 10 | seaborn | 13,404 |
| 11 | ydata-profiling | 13,117 |
| 12 | modin | 10,263 |
| 13 | mlcourse.ai | 10,180 |
| 14 | visidata | 8,429 |
| 15 | ibis | 6,065 |
| 16 | orange | 5,319 |
| 17 | lux | 5,282 |
| 18 | geopandas | 4,861 |
| 19 | Mimesis | 4,612 |
| 20 | alpha_vantage | 4,573 |
| 21 | pytorch-forecasting | 4,455 |
| 22 | missingno | 4,122 |
| 23 | AWS Data Wrangler | 4,054 |
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