Data Manipulation with pandas, Short Course | Part time online | Data Camp | United States
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Short Online

Data Manipulation with pandas

1 days
Duration
Free
Free
Unknown
Tuition fee
Anytime
Unknown
Apply date
Anytime
Unknown
Start date

About

Use the world’s most popular Python data science package to manipulate data and calculate summary statistics. Join the Data Manipulation with pandas course at Data Camp.

Overview

Join over 9 million learners and start Data Manipulation with pandas at Data Camp today!

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!

Programme Structure

Chapters include: 

  • Transforming DataFrames 
  • Slicing and Indexing DataFrames 
  • Aggregating DataFrames 
  • Creating and Visualizing DataFrames

Key information

Duration

  • Part-time
    • 1 days

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Tuition Fee

To always see correct tuition fees
  • International

    Free
    Tuition Fee
    Based on the tuition of 0 USD for the full programme during 1 days.
  • National

    Free
    Tuition Fee
    Based on the tuition of 0 USD for the full programme during 1 days.

Basic Access: Free; Premium (for individuals): $12.42 per month billed annually; Teams: $25 per month billed annually; Enterprise: Contact sales for pricing

Funding

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