Course overview
In this course, you’ll learn how to reduce the memory footprint of a pandas DataFrame while working with data from the Museum of Modern Art. You’ll learn how to work with DataFrame chunks, how to use them to increase processing speed in pandas, and how to optimize DataFrame types while exploring data from the Lending Club. You’ll also learn how to augment pandas with SQLite to combine the best of both tools. Finally, you’ll learn when to use disk space over in-memory space, as well as how to run SQL queries using pandas.
Best of all, you’ll learn by doing – you’ll practice and get feedback directly in the browser. At the end of the course, you’ll complete a project that asks you to work on a real-life example – using the pandas SQLite workflow to analyze startup fundraising deals using data from CrunchBase.
Key skills
- Reducing the memory footprint of a pandas DataFrame
- Processing large DataFrames in chunks using SQLite
Course outline
Processing Large Datasets In Pandas [7 lessons]
Introduction to Pandas 1h
Lesson Objectives- Identify how Pandas uses DataFrames to store data
- Read a CSV into a DataFrame
- Access data from a DataFrame
Calculating With Pandas 1h
Lesson Objectives- Represent 1-dimensional data using pandas
- Perform computations
- Select a subset of data using Boolean masks
- Add new columns to a dataframe
Optimizing DataFrame Memory Footprint 2h
Lesson Objectives- Employ pandas with large datasets
- Identify how much memory pandas datasets use
- Optimize pandas datatypes
Processing Dataframes in Chunks 1h
Lesson Objectives- Employ DataFrame chunks
- Increase processing speed in pandas
Guided Project: Practice Optimizing DataFrames and Processing in Chunks 1h
Lesson Objectives- Expland your portfolio with a DataFrame chunking project
Augmenting Pandas with SQLite 1h
Lesson Objectives- Employ pandas with SQLite
- Determine whether to use disk space or in-memory space
- Run SQL queries using pandas
Guided Project: Analyzing Startup Fundraising Deals from Crunchbase 1h
Lesson Objectives- Run the pandas and SQLite workflow on a new dataset
- Analyze startup fundraising deals using a new workflow
Projects in this course
Practice Optimizing DataFrames and Processing in Chunks
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.
Analyzing Startup Fundraising Deals from Crunchbase
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.
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