Seven Python libraries make up our Python business intelligence toolkit:
- Pandas: A set of high-performance, easy-to-use data structures and data analysis tools. Pandas are the backbone of all our business intelligence tasks.
- Scikit-learn: Gives us simple and efficient tools for data mining and data analysis including classification, regression, clustering, dimensionality reduction, model selection, and preprocessing. This will be the workhorse library for our analysis.
- Numpy: An efficient multi-dimensional container of generic data that allows for arbitrary datatypes to be defined. We won't use numpy directly; however, Pandas relies on it.
- Matplotlib: A 2D plotting library. We'll use this to generate all our charts.
- PyMongo: Allows us to connect to and use MongoDB. We'll use this to insert and retrieve data from MongoDB.
- XlsxWriter: This allows us to access and create Microsoft Excel files. This library will be used to generate reports in the Excel format.
- IPython Notebook (Jupyter): An interactive computational environment. We'll use this to write our code so that we can get feedback faster than running a script over and over again.
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