Data Manipulation in Python: A Pandas Crash Course

Learn how to use Python and Pandas for data analysis and data manipulation. Transform, clean and merge data with Python.

4.18 (1824 reviews)
Udemy
platform
English
language
Data Science
category
instructor
38,662
students
9 hours
content
Mar 2024
last update
$94.99
regular price

What you will learn

Visualise data using methods from histograms to dimensionality reduction.

Create, save and serialise data frames in and out of multiple formats.

Clean and format data easily.

Detect and intelligently fill missing values.

Group, aggregate and summarise your data.

Merge data sources into a beautiful whole.

Pivot and cross-tabulate data like a pro.

Intersplice, summarise and investigate time series data.

Seamlessly work with data from different time zones.

Learn the common pitfalls and traps that ensnare beginners and how to avoid them.

Description

In the real-world, data is anything but clean, which is why Python libraries like Pandas are so valuable.


If data manipulation is setting your data analysis workflow behind then this course is the key to taking your power back.


Own your data, don’t let your data own you!


When data manipulation and preparation accounts for up to 80% of your work as a data scientist, learning data munging techniques that take raw data to a final product for analysis as efficiently as possible is essential for success.


Data analysis with Python library Pandas makes it easier for you to achieve better results, increase your productivity, spend more time problem-solving and less time data-wrangling, and communicate your insights more effectively.


This course prepares you to do just that!


With Pandas DataFrame, prepare to learn advanced data manipulation, preparation, sorting, blending, and data cleaning approaches to turn chaotic bits of data into a final pre-analysis product. This is exactly why Pandas is the most popular Python library in data science and why data scientists at Google, Facebook, JP Morgan, and nearly every other major company that analyzes data use Pandas.


If you want to learn how to efficiently utilize Pandas to manipulate, transform, pivot, stack, merge and aggregate your data for preparation of visualization, statistical analysis, or machine learning, then this course is for you.


Here’s what you can expect when you enrolled with your instructor, Ph.D. Samuel Hinton:


  • Learn common and advanced Pandas data manipulation techniques to take raw data to a final product for analysis as efficiently as possible.

  • Achieve better results by spending more time problem-solving and less time data-wrangling.

  • Learn how to shape and manipulate data to make statistical analysis and machine learning as simple as possible.

  • Utilize the latest version of Python and the industry-standard Pandas library.

Performing data analysis with Python’s Pandas library can help you do a lot, but it does have its downsides. And this course helps you beat them head-on:


1. Pandas has a steep learning curve: As you dive deeper into the Pandas library, the learning slope becomes steeper and steeper. This course guides beginners and intermediate users smoothly into every aspect of Pandas.


2. Inadequate documentation: Without proper documentation, it’s difficult to learn a new library. When it comes to advanced functions, Pandas documentation is rarely helpful. This course helps you grasp advanced Pandas techniques easily and saves you time in searching for help.


After this course, you will feel comfortable delving into complex and heterogeneous datasets knowing with absolute confidence that you can produce a useful result for the next stage of data analysis.


Here’s a closer look at the curriculum:

  • Loading and creating Pandas DataFrames

  • Displaying your data with basic plots, and 1D, 2D and multidimensional visualizations.

  • Performing basic DataFrame manipulations: indexing, labeling, ordering slicing, filtering and more.

  • Performing advanced Pandas DataFrame manipulations: multiIndexing, stacking, hierarchical indexing, pivoting, melting and more.

  • Carrying out DataFrame grouping: aggregation, imputation, and more.

  • Mastering time series manipulations: reindexing, resampling, rolling functions, method chaining and filtering, and more.

  • Merging Pandas DataFrames

Lastly, this course is packed with a cheatsheet and practical exercises that are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice with Pandas too.

Content

BONUSES Get them fast, content will be REMOVED this week

Bonus #1: Special case study: UFO sightings
Bonus #2: Advanced visualisation: Global temperature dataset
Bonus #3: Next level visualisation: Creating animations using matplotlib and ffm
Bonus #4: The connection between SQL and Pandas

Introduction

Introduction
Who Am I? And how to get help
Setting up python and editors
Live Install

Dataset Basics

Finding Datasets
Jupyter Notebooks and Loading Data
Pandas vs Numpy
Creating DataFrames
Saving and Serialising
Inspecting DataFrames

Visual exploration

Introduction and super basic plots
Pandas vs Matplotlib
Visualising 1D distributions
Visualising 2D distributions
Styling Pandas Table outputs
Higher dimension visualisations
Summary

Basic Data Manipulations

Introduction, Labelling and Ordering
Slicing and Filtering
Replacing and Thresholding
Removing and adding data
Apply, map and vectorised functions
Summary

Grouping

Introduction and motivation
Basic grouping syntax
Intelligent imputation
Grouping aggregation
Summary

Merging

Introduction and basic syntax
Different types of merging
Helpful merging functions
Summary

Advanced Manipulation - MultiIndex, Pivoting and more

Introduction and basic MultiIndexes
MultiIndex II - MultiIndex Strikes Back
Stacking and Unstacking
Pivoting
Pivot Margins
Crosstab
Melting
Summary

Time Series Data

Introduction and the Datetime Index
Reindexing
Resampling
Rolling functions
Time Zones
Summary

Conclusion

A recap and a thank you

Screenshots

Data Manipulation in Python: A Pandas Crash Course - Screenshot_01Data Manipulation in Python: A Pandas Crash Course - Screenshot_02Data Manipulation in Python: A Pandas Crash Course - Screenshot_03Data Manipulation in Python: A Pandas Crash Course - Screenshot_04

Reviews

Albert
January 17, 2023
I enjoy the journey, and learn many thing. However some of the terms are so difficult for me to comprehend it. I think I will re-walk through the course again in some times just to catch the meaning. But, the course and the instructor are great, and I have so much fun and get a fantastic lesson, thank you.
Chrysovalantis
December 27, 2022
This course covered properly the necessary concepts and features of Pandas. The course very organized and concise. It started from point A and guided to point B in a pretty straightforward manner. I would also like to add that the exercises along with their solutions in every chapter was a good opportunity to practice and study what one is lacking in order to solve them. Finally, the lecturer is very knowledgeable seems to be someone who has used pandas for hands-on, real-world use cases which help a lot because it helps you understand the importance of the concepts taught in this course and their applicability.
Lisa
December 25, 2022
There are a few issues with the course. Albeit, it contains probably all the info to manipulate data: -it is clearly a course for INTERMEDIATE learners - knowledge of basic/advanced syntax is taken completely for granted -the most problematic issue of the course is the speed since the teacher speaks and types really fast -the teacher keeps rewriting and changing the code just presented on screen augmenting the chance of confusion and the need to pause It might be useful as a refresher to someone who has already studied these topics, but not for the ones that are approaching the subject for the first time...unless you want to pause every three seconds. The only way to get through some sections was by having an experienced friend by my side.
Gintare
December 18, 2022
excellent course for busy people but you need friend that can help you with some stuff when its not clear.
Christopher
December 12, 2022
The course is heading in a good direction right from the start. And Sam the instructor is fun to listen to.
Adrian
December 9, 2022
Great teacher! Structure of content and language used to transfer content is perfect - great course so far.
Jay
November 7, 2022
I would not recommend this course for absolute beginners, but it has some good review material for users who are somewhat familiar with Pandas. This course shows that there can be multiple ways to accomplish the same task, which is helpful to know.
Nicholas
September 13, 2022
There wasn't much room for "hands-on" work during this course. You basically just watch and listen as the instructor does everything.
Trần
September 8, 2022
Really good course, detail and well explanation, the only 1 problem is the course, teacher talking run so fast
Francisco
September 5, 2022
Overall great work, but the presentation is too quick, as if the viewer is recalling something rather than learning it.
Gleb
July 23, 2022
It is a crash course as the name suggests. To get anything out of the course one needs to be very familiar with Python and data analytics packages (Pandas, Numpy etc.) already. The author runs through some basic Pandas, Numby and charting functions at an extremely fast pace. I would've scored higher if the author slowed down a bit to explain a bit better how these functions work, i.e. a bit more detail about arguments etc.
Ying
July 15, 2022
I definitely learned a lot through this course. It is the best Pandas course ever. And Sam also showed how to customize the Jupyter notebook which is pretty cool. I loved it
Amanda
June 29, 2022
This course covers a vast amount of very useful information for data analysis with Pandas. That being said, the one slight negative is that the instructor flies through it all super fast. I know he does this to cover as many things as possible in a reasonable amount of time. Some people may love that about this course, and others may find they need to pause and/or rewind to listen again to explanations that were given very quickly. Still, it was a very good course and I learned a lot!
Ira
May 25, 2022
Excellent topic coverage, although subjects are covered quickly, so may require watching more than once. That said the instructor chose many different interesting data sets and keeps the attention using humor. Overall, I highly recommend for learning data manipulation, cleaning and creating sharp plots to show insights with very efficient, clean code examples.
Witold
March 27, 2022
Had a great time doing this course, highly recommended! Basic pandas concepts taught clearly and concisely with good examples. I really enjoyed that after every chapter there's an additional exercise to do to deepen the learning. Was good fun to listen to Sam too:)

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2860646
udemy ID
3/9/2020
course created date
3/21/2020
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