Data Analysis in Python with Pandas

Getting an introduction to doing data analysis with the Python pandas library with hours of video and code.

3.80 (760 reviews)

Udemy

platform

English

language

Software Engineering

What you will learn

Perform data analysis with python using the pandas library.

Understand some of the basic concepts of data analysis.

Have used n-dimensional arrays in NumPy as well as the pandas Series and DataFrames to analyze data.

Learned the basics of plotting with matplotlib

Why take this course?

Ever wonder how you can best analyze data in python? Wondering how you can advance your career beyond doing basic analysis in excel? Want to take the skills you already have from the R language and learn how to do the same thing in python and pandas?

THEN THIS COURSE IS FOR YOU!

By taking the course, you will master the fundamental data analysis methods in python and pandas!

You’ll also get access to all the code for future reference, new updated videos, and future additions for FREE! You'll Learn the most popular Python Data Analysis Technologies!

By the end of this course:

- Understand the data analysis ecosystem in Python.

- Learn how to use the pandas data analysis library to analyze data sets

- Create how to create basic plots of data using MatPlotLib

- Analyze real datasets to better understand techniques for data analysis

At the end of this course you will have learned a lot of the tips and tricks that cut down my learning curve as a business analyst and as a Master’s Student at UC Berkeley doing data analysis. I designed this course for those that have an intermediate programming ability and are ready to take their data analysis skills to the next level.

You’ll understand cutting edge techniques used by data analysts, data scientists, and other data researches in Silicon Valley.

Complete with working files and code samples, over 5 hours with 40+ lectures you’ll learn all that you need to know to turn around and apply data analysis strategies to the data that you work with. You’ll be able to work along side the instructor as we work through different data sets and data analysis approaches using cutting edge data science tools!

Reviews

Rory

April 25, 2022

He explains the "how" of doing things, but not the "why". For example, it would be better to show an analysis function by introducing it as a "way of ..." Unless, you are already familiar with "why" learning the "how" makes it very hard to stay motivated in the course.

Vinh

January 11, 2017

clear explanations and follow through. Good notes. However, i'd appreciate more if we have a lot of exercises tailored in the lectures. Suggestion would be a couple of exercises for each new concept; so slow learners can feel comfortable with them! Keep up the good work!

Alex

January 5, 2017

Good course. Miss more interactivity or concrete exercises on what's just learned. Sound is too low :) And update code to new versions. Overall very good, I learned a lot

John

December 26, 2016

Very clear and thorough instruction. A fast paced way to follow along in Jupyter and learn the methods!

Gale

November 25, 2016

It is a very basic Numpy and Pandas course. However, I can't figure out what is the business application / practical application of this course. Where in a business world this knowledge is used? Also, why would I use Pandas instead of SAS Statistical Language? Or why would I use Pandas instead of SQL Queries? I think if I had more business examples I would be able to appreciate Numpy and Pandas more.

Andrei

November 10, 2016

Good structured course, however some users use Python 3 so there are some mismatches between Python 2 and 3. Well structured course is highly recommended for data scientists , accountancy departments and back offices. Thank you .

Mags

November 3, 2016

A good course, covers a lot of topics and most of them are explained in a clear manner. Accompanying notebooks are very useful. Two cons though: 1. I wish there was more exercises so that students could practice newly learned skills. 2. It seems that the instructor doesn't answer questions anymore.

David

October 25, 2016

This course is composed of a series of clear, concise demonstrations of the key Pandas datatypes and functions. They are easy to follow and well explained.

Craig

October 19, 2016

The course started out great, but the author sort of gave up on the last 2 modules. Videos end suddenly, some titles say "Insert Title Here" and just overall lack of attention to detail. He still knows the topic, but could have put in a little more effrt int he videos.

Charles

October 16, 2016

Excellent course that provides a good first look into Pandas, as well as great information regarding some of the deeper levels of Pandas. I definitely learned a lot, and now feel comfortable working in pandas as well as jupyter notebooks!

Sujay

October 8, 2016

The course is very precise and too the point explaining applied concepts and useful functions/methods. The course is very focused and relatively short to complete. I would have liked to see some more theory or deep dive to be explained in two 10 min videos to make this course complete. Also if there are some practical examples or case studies thrown in, that would be great.

Graham

September 10, 2016

Great content. But presentation sometimes not ideal - ie cant see typing in some videos so verbal descriptions doesnt match what it on screen

Ktawut

August 27, 2016

The tutorial is based on Python 2.7. At the time of writing we have Python 3.5 already. The materials should be updated since some method signatures / libraries have been deprecated. Learners should be cautious.

Krzysztof

August 16, 2016

Great content and very good delivery. I would add more quizzes and exercises. Sometimes, fortunately not too often, I am not sure why this particular function or method is mentioned. I prefer format, where the problem is stated and then the solution is given using content of the course. I would as well advise to use video editing software to deliver smooth uninterrupted lecture.

Kamal

July 24, 2016

Good run through of numpy and Pandas methods. I think the advanced topics might have benefitted from a little more depth and explanation as they are syntantically dense and not intuitive at times (groupby etc).

Charts

Price

Rating

Enrollment distribution

Data Analysis in Python with Pandas - Distribution chart