Python for Finance Cookbook

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In this recipe, we introduced a range of possible approaches to investigate the data at hand. However, this requires many lines of code each time we want to carry out the EDA. Thankfully, there is a Python library that simplifies the process. The library is called pandas_profiling and, with a single line of code, it generates a comprehensive summary of the dataset in the form of an HTML report.

To create a report, we need to run the following:

import pandas_profilingdf.profile_report()

For brevity, we only mention some selected elements of the report:

• An overview giving information about the size of the DataFrame (number of features/rows, missing values, duplicated rows, memory size, breakdown per data type)
• A list of warnings, ...