Appendix: Python Packages

Contents

Appendix: Python Packages¶

The following is general overview of packages available in Python that may be useful for data science.

For a much broader / fuller list of the Python ecosystem, check out the Awesome Python list.

Data-Science Modules¶

These are all external (non-standard library) packages. Many of them are available in the Ananconda distribution.

Core Packages¶

scipy - mathematics, science, and engineering.
numpy - numerical computing with arrays & array operations.
pandas - data structures and data analysis.
scikit-learn - machine learning and data analysis.

Text Mining¶

nltk - natural language processing.
gensim - topic modelling.

Mathematics & Statistics¶

sympy - symbolic mathematics.
statsmodels - statistical modelling.

Web Scraping¶

requests - HTTP requests.
scrapy - web scraping.

Plotting / Vizualization Libraries¶

matplotlib - 2D plotting library.
seaborn - visualization (based on matplotlib).
bokeh - interactive visualizations.

Graph Theory / Networks¶

networkx - network analysis.
graph-tool - manipulation and analysis of graphs.

Deep Learning¶

theano - mathematical operations on multi-dimensional arrays.
tensorflow - numerical computation using data flow graphs.
keras - a high-level neural network library.

Useful parts of the standard library¶

The full list of packages in the standard library is available here.

Basic Utilities¶

os - miscellaneous operating system operations.
sys - system operations.
datetime - manipulating dates & times.
glob - searching path names.

Useful Functions¶

math - mathematical functions.
random - (pseudo) random number generators.
re - regular expressions.

File Formats¶

json - support for working with JSON files.
csv - support for working with CSV files.

Data Objects¶

collections - container data types.
pickle - serializing & de-serializing (saving and loading complex objects).

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Natural Language Processing

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Appendix: Version Control