Data Manipulation with pandas

Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.
Start Course for Free
4 Hours15 Videos56 Exercises131,416 Learners
4850 XP

Create Your Free Account

GoogleLinkedInFacebook
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA. You confirm you are at least 16 years old (13 if you are an authorized Classrooms user).

Loved by learners at thousands of companies


Course Description

pandas is the world's most popular Python library, used for everything from data manipulation to data analysis. In this course, you'll learn how to manipulate DataFrames, as you extract, filter, and transform real-world datasets for analysis. Using pandas you’ll explore all the core data science concepts. Using real-world data, including Walmart sales figures and global temperature time series, you’ll learn how to import, clean, calculate statistics, and create visualizations—using pandas to add to the power of Python!

  1. 1

    Transforming DataFrames

    Free
    Let’s master the pandas basics. Learn how to inspect DataFrames and perform fundamental manipulations, including sorting rows, subsetting, and adding new columns.
    Play Chapter Now
  2. 2

    Aggregating DataFrames

    In this chapter, you’ll calculate summary statistics on DataFrame columns, and master grouped summary statistics and pivot tables.
    Play Chapter Now
  3. 3

    Slicing and Indexing DataFrames

    Indexes are supercharged row and column names. Learn how they can be combined with slicing for powerful DataFrame subsetting.
    Play Chapter Now
  4. 4

    Creating and Visualizing DataFrames

    Learn to visualize the contents of your DataFrames, handle missing data values, and import data from and export data to CSV files.
    Play Chapter Now
In the following tracks
Data Analyst Data Manipulation Data Scientist Python Programmer
Collaborators
Alex YaroshAdel NehmeAmy PetersonJustin Saddlemyer
Prerequisites
Intermediate Python
Richie Cotton Headshot

Richie Cotton

Curriculum Architect at DataCamp
Richie is a Learning Solutions Architect at DataCamp. He has been using R since 2004, in the fields of proteomics, debt collection, and chemical health and safety. He has released almost 30 R packages on CRAN and Bioconductor – most famously the assertive suite of packages – as well as creating and contributing to many others. He also has written two books on R programming, Learning R and Testing R Code.
See More
Maggie Matsui Headshot

Maggie Matsui

Curriculum Manager at DataCamp
Maggie is a Curriculum Manager at DataCamp. She holds a Bachelor's degree in Statistics and Computer Science from Brown University, where she spent lots of time teaching math, programming, and statistics as a tutor and teaching assistant. She's passionate about teaching all things data-related and making programming accessible to everyone.
See More

What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA