Datacamp – Data Manipulation with Python 2024-8

Datacamp – Data Manipulation with Python 2024-8 Downloadly IRSpace

Datacamp – Data Manipulation with Python 2024-8
Datacamp – Data Manipulation with Python 2024-8

Data Manipulation with Python, Real-world data is messy. That’s why libraries like pandas are so valuable. Using pandas, you can take the pain out of data manipulation by extracting, filtering, and transforming data in DataFrames, clearing a path for quick and reliable data analysis. If you want to improve your data wrangling skills, this is the track for you. You’ll learn how to prepare real-world data for analysis and grow your expertise as you work with multiple DataFrames using pandas. You’ll also gain hands-on experience of how to combine, merge, and create visualizations. At the end of the track, you’ll learn all about NumPy arrays and use New York City’s tree census data to create, sort, filter, and update arrays. Start this track and discover how pandas and NumPy can save you time manipulating data.

What you’ll learn

  • Learn how to import and clean data, calculate statistics, and create visualizations with pandas.
  • Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.
  • Learn to combine data from multiple tables by joining data together using pandas.
  • Master your skills in NumPy by learning how to create, sort, filter, and update arrays using NYC’s tree census.

Specificatoin of Data Manipulation with Python

  • Publisher : Datacamp
  • Teacher : Maggie Matsui
  • Language : English
  • Level : All Levels
  • Number of Course : 4
  • Duration: 16h

Content of Data Manipulation with Python

Data Manipulation with Python

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Data Manipulation with Python

Sample Clip

Installation Guide

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Subtitle : English

Quality: 720p

Download Links

Data Manipulation with pandas

Download – 70 MB

Introduction to NumPy

Download – 67 MB

Joining Data with pandas

Download – 86 MB

Reshaping Data with pandas

Download – 81 MB

File size

306 MB