Udemy

Data Analysis Crash Course For Beginners (Pandas + Python)

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  • 1,892 Students
  • Updated 11/2023
4.3
(51 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
1 Hour(s) 3 Minute(s)
Language
English
Taught by
Shubham Sarda
Rating
4.3
(51 Ratings)
3 views

Course Overview

Data Analysis Crash Course For Beginners (Pandas + Python)

Take First Step Toward Data Analysis With Pandas - Learn about DataFrames, Jupyter Notebook, iPython and Pandas Commands

Welcome to Data Analysis Basics with Pandas and Python - For Beginners,
This course will help you to understand the fundamentals of Data Analysis with Python and Pandas library. You will learn,

1. Fundamentals of Data Analysis.

2. Working with Pandas, iPython, Jupyter Notebook.

3. Important Jupyter Notebook Commands.

4. Working with CSV, Excel, TXT, JSON Files and API Responses.

5. Working with DataFrames (Indexing, Slicing, Adding and Deleting).

Pandas is an open-source library providing high-performance, easy-to-use data structures and data analysis tools for Python. Pandas provide a powerful and comprehensive toolset for working with data, including tools for reading and writing diverse files, data cleaning and wrangling, analysis and modelling, and visualization. Fields with the widespread use of Pandas include data science, finance, neuroscience, economics, advertising, web analytics, statistics, social science, and many areas of engineering.

After completing this course you will have a good understanding of Pandas and will be ready to explore Data Analysis in-depth in future.

Course Content

  • 5 section(s)
  • 13 lecture(s)
  • Section 1 Course Introduction
  • Section 2 What is Pandas?
  • Section 3 Jupyter Notebooks
  • Section 4 Working on Data
  • Section 5 Bonus - What's Next?

What You’ll Learn

  • Fundamentals of Data Analysis., Working with Pandas, iPython, Jupyter Notebook., Important Jupyter Notebook Commands., Working with CSV, Excel, TXT, JSON Files and API Responses., Working with DataFrames (Indexing, Slicing, Adding and Deleting).


Reviews

  • A
    Avanish K Yadav
    4.0

    Its good to learn and go ahead

  • S
    Sujeet Suresh Ghorpade
    5.0

    Course was good and able to understand.

  • N
    Naveen Reddy
    4.5

    good

  • A
    Alifiya Shaikh
    4.0

    Yes , it is good and explanation is also simple

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