Complete Data Wrangling & Data Visualisation With Python

Learn to Preprocess, Wrangle and Visualise Data For Practical Data Science Applications in Python

4.26 (913 reviews)
Udemy
platform
English
language
Data Science
category
instructor
15,456
students
6.5 hours
content
Nov 2023
last update
$64.99
regular price

What you will learn

Install and Get Started With the Python Data Science Environment- Jupyter/iPython

Read In Data Into The Jupiter/iPython Environment From Different Sources

Carry Out Basic Data Pre-processing & Wrangling In the Jupyter Environment

Learn to IDENTIFY Which Visualisations Should be Used in ANY given Situation

Go From A Basic Level To Performing Some Of The MOST COMMON Data Preprocessing, Data Wrangling & Data Visualization Tasks In Jupyter

How To Use Some Of The MOST IMPORTANT Data Wrangling & Visualisation Packages Such As Matplotlib

Build POWERFUL Visualisations and Graphs from REAL DATA

Apply Data Visualization Concepts For PRACTICAL Data Analysis & Interpretation

Gain PROFICIENCY In Data Preprocessing, Data Wrangling & Data Visualisation In Jupyter By Putting Your Soon-To-Be-Acquired Knowledge Into IMMEDIATE Application

Description

Hello, My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment) graduate. I recently finished a PhD at Cambridge University (Tropical Ecology and Conservation).


I have several years of experience in analyzing real life data from different sources using statistical modeling and producing publications for international peer reviewed journals. If you find statistics books & manuals too vague, expensive & not practical, then you’re going to love this course!

I created this course to take you by hand and teach you all the concepts, and tackle the most fundamental building block on practical data science- data wrangling and visualisation.

 

GET ACCESS TO A COURSE THAT IS JAM PACKED WITH TONS OF APPLICABLE INFORMATION!


This course is your sure-fire way of acquiring the knowledge and statistical data analysis wrangling and visualisation skills that I acquired from the rigorous training I received at 2 of the best universities in the world, perusal of numerous books and publishing statistically rich papers in renowned international journal like PLOS One.

To be more specific, here’s what the course will do for you:


  (a) It will take you (even if you have no prior statistical modelling/analysis background) from a basic level to performing some of the most common data wrangling tasks in Python.


  (b) It will equip you to use some of the most important Python data wrangling and visualisation packages such as seaborn.


  (c) It will Introduce some of the most important data visualisation concepts to you in a practical manner such that you can apply these concepts for practical data analysis and interpretation.

 

  (d) You will also be able to decide which wrangling and visualisation techniques are best suited to answer your research questions and applicable to your data and interpret the results.

 

The course will mostly focus on helping you implement different techniques on real-life data such as Olympic and Nobel Prize winners


After each video you will learn a new concept or technique which you may apply to your own projects immediately! Reinforce your knowledge through practical quizzes and assignments.

 

TAKE ACTION NOW :) You’ll also have my continuous support when you take this course just to make sure you’re successful with it.  If my GUARANTEE is not enough for you, you can ask for a refund within 30 days of your purchase in case you’re not completely satisfied with the course.

TAKE ACTION TODAY! I will personally support you and ensure your experience with this course is a success.

Content

INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools

Welcome to the Course
Data & Script For the Course
Python Data Science Environment
For Mac Users
Introduction to IPython/Jupyter
ipython in Browser

Read in Data From Different Sources With Pandas

What are Pandas?
Read CSV Data
Read Excel Data
Read in HTML Data

Data Cleaning

Remove NA Values
Missing Values in a Real Dataset
Data Imputation
Imputing Qualitative Values
Use k-NN for Data Imputation

Basic Data Wrangling

Basic Principles
Preliminary Data Explorations
Basic Data Handling With Conditional Statements
Drop Column/Row
Change Column Name
Change the Column Type
Explore Date Related Data
Simple Date Related Computations

More Data Wrangling

Data Grouping
Data Subsetting and Indexing
More Data Subsetting
Extract Information From Strings
(Fuzzy) String Matching
Ranking & Sorting
Concatenate
Merging and Joining

Feature Selection and Transformation

Correlation Analysis
Using Correlation to Decide Which Features to Retain
Univariate Feature Selection
Recursive Feature Elimination (RFE)
Theory Behind PCA
Implement PCA
Data Standardisation
Create a New Feature

Theory Behind Data Visualisation

What is Data Visualisation?
Some Theoretical Principles Behind Data Visualisation

Most Common Data Visualizations

Histograms-Visualize the Distribution of Continuous Numerical Variables
Boxplots-Visualize the Distribution of Continuous Numerical Variables
Scatter plot-Relationship Between Two Numerical Variables
Barplot
Pie Chart
Line Charts
More Line Charts
Some More Plot Types
And Some More

Miscallaneous Information

Using Colabs as an Online Jupyter Notebook

Screenshots

Complete Data Wrangling & Data Visualisation With Python - Screenshot_01Complete Data Wrangling & Data Visualisation With Python - Screenshot_02Complete Data Wrangling & Data Visualisation With Python - Screenshot_03Complete Data Wrangling & Data Visualisation With Python - Screenshot_04

Reviews

Rossey
October 13, 2023
The instructor has impressive knowledge of the concept and has explained finer details of the subject lucidly and unambiguously.
Vipin
October 12, 2023
The instructor has brilliantly explained the utility of Python for data wrangling and data visualization.
Jordi
August 4, 2023
The examples in the HTML reading section don't work. Seems like the HTML structure has changed, so the scritps and examples shown do not work at all.
Mamta
July 26, 2023
The course has immense potential for practical use as it contains valuable and updated information on the subject.
Mukesh
July 25, 2023
This is a comprehensive course explaining the use of Python for data wrangling and data visualization.
Jaskaran
May 9, 2023
The instructor's presentation of usage of Python for data wrangling and data visualization is excellent. Her knowledge of the subject is impressive.
Kamlesh
April 15, 2023
The instructor is at her best in explaining the use and importance if Python for data wrangling and data analysis.
Deependra
December 27, 2022
The instructor has very lucidly and effectively explained the utility of Python for data wrangling and data visualisation.
Yash
November 25, 2022
somewhere you are missing complete screen (in few lectures i watched only half screen in jupyter notebook) which is creating disturbance in focus.
Adam
November 22, 2022
Simple stuff got explained in detail and complicated stuff got a bare mention (random forest, regular expressions, or any function with a significant variety of flags).
Justin
October 13, 2022
This course is a lot of info, and in order to retain it there should be both exercises to help practice the skills and/or links to online notebooks where you can copy/note key parts that you want to come back to
Carlos
October 10, 2022
I like that the instructor is starting slow and making sure people are comfortable with the environment we will be working in: Anaconda. I also like that she shows multiple ways to access what we need.
Krishnappa
August 27, 2022
The instructor is her best in presenting such an important course on data processing wrangling and visualization,
Neeraj
July 22, 2022
Instructor have very good knowledge, skill is also excellent. The course is beyond my expectations.
Rajesh
June 23, 2022
The course is ideally suited for my work. It will certainly enhance the quality of my work several notches.

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DateDiscountStatus
5/19/2019100% OFF
expired
8/25/202379% OFF
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2079358
udemy ID
12/10/2018
course created date
5/19/2019
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