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Joining Data with pandas

Intermediate
4.3+
153 reviews
Updated 12/2024
Learn to combine data from multiple tables by joining data together using pandas.
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PythonData Manipulation4 hours15 videos51 exercises4,050 XP166,950Statement of Accomplishment

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Course Description

Being able to combine and work with multiple datasets is an essential skill for any aspiring Data Scientist. pandas is a crucial cornerstone of the Python data science ecosystem, with Stack Overflow recording 5 million views for pandas questions. Learn to handle multiple DataFrames by combining, organizing, joining, and reshaping them using pandas. You'll work with datasets from the World Bank and the City Of Chicago. You will finish the course with a solid skillset for data-joining in pandas.

Prerequisites

Data Manipulation with pandas
1

Data Merging Basics

Start Chapter
2

Merging Tables With Different Join Types

Start Chapter
3

Advanced Merging and Concatenating

Start Chapter
4

Merging Ordered and Time-Series Data

Start Chapter
Joining Data with pandas
Course
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Don’t just take our word for it

*4.3
from 153 reviews
59%
22%
14%
3%
2%
  • Carlos M.
    16 days

    The course was good

  • Thomas K.
    19 days

    Pandas in Python is likely one of the first packages you encounter in the Python universe, and one of the most powerful. Similar in functionality with dplyr in R, it can do pretty much any data wrangling task you throw at it. By taking this course at DataCamp, you build up your data manipulation skills step by step, gaining data analysis confidence along the way.

  • Johan K.
    27 days

    DataCamp's Python for Data Analysis courses are great to learn both Python and Data Analysis. The code is illustrated with the theory and the other way around. Read the excersize carefully to minimize errors in your code!

  • Carlos E.
    29 days

    .

  • P. T.
    about 1 month

    Great learning..Easy to understand

"The course was good"

Carlos M.

"DataCamp's Python for Data Analysis courses are great to learn both Python and Data Analysis. The code is illustrated with the theory and the other way around. Read the excersize carefully to minimize errors in your code!"

Johan K.

"."

Carlos E.

FAQs

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