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Data Manipulation with pandas

Learn how to import and clean data, calculate statistics, and create visualizations with pandas.

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4 Hours15 Videos56 Exercises244,285 Learners4850 XPData Analyst TrackData Manipulation TrackData Scientist TrackPython Programmer Track

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Course Description

Discover Data Manipulation with pandas

With this course, you’ll learn why pandas is the world's most popular Python library, used for everything from data manipulation to data analysis. You’ll explore how to manipulate DataFrames, as you extract, filter, and transform real-world datasets for analysis.

With 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.

Work with pandas Data to Explore Core Data Science Concepts

You’ll start by mastering the pandas basics, including how to inspect DataFrames and perform some fundamental manipulations. You’ll also learn about aggregating DataFrames, before moving on to slicing and indexing.

You’ll wrap up the course by learning how to visualize the contents of your DataFrames, working with a dataset that contains weekly US avocado sales.

Learn to Manipulate DataFrames

By completing this pandas course, you’ll understand how to use this Python library for data manipulation. You’ll have an understanding of DataFrames and how to use them, as well as be able to visualize your data in 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
    Introducing DataFrames
    50 xp
    Inspecting a DataFrame
    100 xp
    Parts of a DataFrame
    100 xp
    Sorting and subsetting
    50 xp
    Sorting rows
    100 xp
    Subsetting columns
    100 xp
    Subsetting rows
    100 xp
    Subsetting rows by categorical variables
    100 xp
    New columns
    50 xp
    Adding new columns
    100 xp
    Combo-attack!
    100 xp

In the following tracks

Data Analyst Data Manipulation Data Scientist Python Programmer

Collaborators

alexandrayarosh
Alex Yarosh
AAN94
Adel Nehme
amy-4121b590-cc52-442a-9779-03eb58089e08
Amy Peterson
justin-saddlemyer
Justin Saddlemyer

Prerequisites

Intermediate Python
Richie Cotton Headshot

Richie Cotton

Data Evangelist at DataCamp

Richie is a Data Evangelist 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.
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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.
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