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Useful Pandas csv import functions. Original by Chris Albon

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Aabehmiel
Last edited Apr 18, 2017
Created on Apr 18, 2017

This example demonstrates multiple ways to import CSV data into pandas DataFrames, highlighting how to handle missing values, specify column names, set indexes, skip rows, and interpret thousands separators. The code creates a sample dataset with mixed data types—including strings, integers, and missing values marked with periods—then saves it as a CSV file before applying various `pd.read_csv` parameters. It shows techniques like using `header=None`, the `names` parameter, `index_col` for single or multi-column indexes, `na_values` for custom missing value sentinels, `skiprows` to omit initial lines, and `thousands=','` to parse formatted numbers. The examples use pandas' built-in CSV reader, sourced from Chris Albon's original tutorial.

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