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Streamlined Data Ingestion with pandas

4.5+
12 reviews
Intermediate

Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.

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4 Hours16 Videos53 Exercises
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Course Description

Before you can analyze data, you first have to acquire it. This course teaches you how to build pipelines to import data kept in common storage formats. You’ll use pandas, a major Python library for analytics, to get data from a variety of sources, from spreadsheets of survey responses, to a database of public service requests, to an API for a popular review site. Along the way, you’ll learn how to fine-tune imports to get only what you need and to address issues like incorrect data types. Finally, you’ll assemble a custom dataset from a mix of sources.
  1. 1

    Importing Data from Flat Files

    Free

    Practice using pandas to get just the data you want from flat files, learn how to wrangle data types and handle errors, and look into some U.S. tax data along the way.

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    Introduction to flat files
    50 xp
    Get data from CSVs
    100 xp
    Get data from other flat files
    100 xp
    Modifying flat file imports
    50 xp
    Import a subset of columns
    100 xp
    Import a file in chunks
    100 xp
    Handling errors and missing data
    50 xp
    Specify data types
    100 xp
    Set custom NA values
    100 xp
    Skip bad data
    100 xp
  2. 4

    Importing JSON Data and Working with APIs

    Learn how to work with JSON data and web APIs by exploring a public dataset and getting cafe recommendations from Yelp. End by learning some techniques to combine datasets once they have been loaded into data frames.

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Data Engineer

Collaborators

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Hillary Green-Lerman
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Adrián Soto
Amany Mahfouz HeadshotAmany Mahfouz

Data scientist via spatial analytics and geography.

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Don’t just take our word for it

*4.5
from 12 reviews
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  • Faria C.
    27 days

    This course has many useful tips for handling type conversions such as datetimes and booleans. The chapter on parsing nested JSON from an API is very helpful, and I have already put it to use.

  • Lorenzo A.
    about 2 months

    Good

  • Sorin I.
    11 months

    Great content and practice mode. Concise and easy to follow, very useful.

  • Victor G.
    12 months

    Excellent course

  • Erick S.
    12 months

    Quite fluid course, straight to the point, clear examples.

"This course has many useful tips for handling type conversions such as datetimes and booleans. The chapter on parsing nested JSON from an API is very helpful, and I have already put it to use."

Faria C.

"Good"

Lorenzo A.

"Great content and practice mode. Concise and easy to follow, very useful."

Sorin I.

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