Clahe pipeline cellprofiler3/28/2023 Spark - DataFrame for big data, cheatsheet, tutorial. Textract - Extract text from any document.Ĭamelot - Extract text from PDF. Intake - Loading datasets made easier, talk. Pyprojroot - Helpful here() command from R. Helpfulĭrawdata - Quickly draw some points and export them as csv, website. Scikit-learn-intelex - Intel extension for scikit-learn for speed. Polars - Multi-threaded alternative to pandas.ĭuckdb - Efficiently run SQL queries on pandas DataFrame. Lux - DataFrame visualization within Jupyter.ĭtale - View and analyze Pandas data structures, integrating with Jupyter. Pandapy - Additional features for pandas. Pandas-log - Find business logic issues and performance issues in pandas. Pandas_flavor - Write custom accessors like. Swifter - Apply any function to a pandas DataFrame faster. Xarray - Extends pandas to n-dimensional arrays. Pandarallel - Parallelize pandas operations. Modin - Parallelization library for faster pandas DataFrame. Pandasvault - Large collection of pandas tricks. Pandas Tricks, Alternatives and Additions Voila - Turn Jupyter notebooks into standalone web applications. Notebooker - Productionize and schedule Jupyter Notebooks. Handcalcs - More convenient way of writing mathematical equations in Jupyter. Nbcommands - View and search notebooks from terminal. Jupyter-datatables - Interactive tables in Jupyter. Pivottablejs - Drag n drop Pivot Tables and Charts for Jupyter notebooks. RISE - Turn Jupyter notebooks into presentations. Nbdime - Diff two notebook files, Alternative GitHub App: ReviewNB. Papermill - Parameterize and execute Jupyter notebooks, tutorial. Nteract - Open Jupyter Notebooks with doubleclick. Pyscaffold - Python project template generator. Python debugger (pdb) - blog post, video, cheatsheet Xonsh - Python-powered shell as alternative to Bash for simplifying data science automations. Sklearn_pandas - Helpful DataFrameMapper class. Pandas_profiling - Descriptive statistics using ProfileReport. Seaborn - Data visualization library based on matplotlib.ĭatatile - Basic statistics using DataFrameSummary(df).summary(). Pandas - Data structures built on top of numpy. ![]() A curated list of awesome resources for practicing data science using Python, including not only libraries, but also links to tutorials, code snippets, blog posts and talks.
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