Saving & Loading CSV Files with Pandas DataFrames

Pandas DataFrames provide convenient methods for manipulating data with ease. The row-column format of the DataFrame is native to CSV files and knowing how to both save and load CSV files with Pandas is an essential skill for any data scientist!

Zack West
alpharithms

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picture of loading a csv file as a DataFrame object by alpharithms
Image: alpharithms

Pandas is a powerful data science library with heavy optimizations done. The DataFrame object is an efficient data structure whereby data is organized in a 2-dimensional manner with powerful built-in tools for manipulating that data.

The Pandas DataFrame object is useful for displaying, analyzing, and manipulating tabulated data such as spreadsheets. However, sometimes viewing the data can be burdensome in a terminal. In this quick tutorial, we’ll convert a Pandas DataFrame object into a local CSV file for convenient viewing in other programs as well as data storage.

Highlights

By the end of this tutorial, we will have covered the following:

  1. Fetching remote pricing data via the yfinance library as a DataFrame object.
  2. Saving the DataFrame to a local CSV file.
  3. Loading the local CSV file as a DataFrame.

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Zack West
alpharithms

Entrepreneur, programmer, designer, and lifelong learner. Can be found taking notes from Mother Nature when not hammering away at the keyboard.