Course · Intermediate

Processing Large Datasets In Pandas

In this course, you'll learn how to work with medium-sized datasets by optimizing your pandas workflow, processing data in batches, and augmenting pandas with SQLite.

  • Intermediate friendly
  • 5 hrs
  • 5 lessons
  • 2 projects
  • Premium

Course overview

Optimize pandas workflows to handle larger datasets by reducing memory usage, processing data in chunks, and combining pandas with SQLite.

What's inside

5 lessons · 2 projects

  • 01
    Optimizing DataFrame Memory Footprint

    Learn how to reduce a Dataframe's memory footprint by selecting the correct data types

    78 min
  • 02
    Processing Dataframes in Chunks

    Learn how to break a problem down into DataFrame chunks.

    53 min
  • 03
    Guided Project: Practice Optimizing DataFrames and Processing in Chunks Project

    For this project, we'll step into the role of data engineers to optimize a DataFrame's memory footprint and process a large dataset of loan data in chunks using Python and pandas.

    25 min
  • 04
    Augmenting Pandas with SQLite

    Learn the pandas SQLite workflow to combine the best of both tools.

    34 min
  • 05
    Guided Project: Analyzing Startup Fundraising Deals from Crunchbase Project

    For this project, we'll step into the role of data analysts to explore a dataset of startup investments from Crunchbase. We'll practice techniques to work with larger datasets and gain insights into fundraising trends.

    10 min
  • 06
    Introduction to Pandas

    Learn how to read data into Pandas and how to access it.

    44 min
  • 07
    Calculating With Pandas

    Learn how to perform calculations using Pandas.

    43 min

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