Explore and Analyze Data with Python || Live Coding Session

Looking to level up your data skills? Tap in for an exciting virtual workshop where you’ll learn how to conduct Exploratory Data Analysis (EDA) using Python's powerhouse libraries like NumPy, Pandas, and Matplotlib!

👩‍💻 What you’ll learn:
Crunch numbers with NumPy and Pandas
Create stunning data visualizations with Matplotlib

Let’s dive into the world of data together! 🔢📈📊

Follow us on our socials to join one of our live workshops: https://linktr.ee/uon_codingclub

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Session Resources:

GitHub Repo
https://github.com/0gregory0/Explore-...

Explore and analyze data with Python
https://learn.microsoft.com/training/...

Python for Data Science
https://learn.microsoft.com/training/...

Python for Beginners
https://learn.microsoft.com/training/...

Get Started with Jupyter Notebooks for Python
https://learn.microsoft.com/training/...

GitHub Foundations
https://learn.microsoft.com/training/...

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0:00 - Meeting starts
7:16 - Introduction
8:08 - Prereqs
9:43 - About MS Learn [https://learn.microsoft.com?wt.mc_id=studentamb_206118]
11:55 - About Me
12:53 - Relevance of EDA in Data Science
13:13 - Lesson Objectives
13:33 - EDA Prerequisites
14:15 - Introduction to Exploratory Data Analysis
15:38 - Example Scenario
19:10 - NumPy, Pandas & Jupyter notebooks intro
23:53 - How to use a Jupyter Notebook
25:53 - Basics of NumPy
27:28 - NumPy Arrays
30:00 - Difference between List and Array
35:12 - array.shape attribute
36:25 - Array indexing
37:30 - NumPy Methods
38:20 - 2D NumPy Arrays
41:41 - Indexing 2D Arrays
43:50 - Basics of Pandas
46:25 - Reading CSV files
49:35 - Filtering a dataframe: loc and iloc
56:20 - Pandas Dataframe vs Pandas Series
58:20 - loc and iloc
1:08:28 - When Pandas gets confusing
1:12:03 - Handling Missing Values
1:14:07 - Detecting missing values
1:18:20 - Imputing the mean
1:20:41 - Exploring the Dataframe
1:41:05 - Data Visualization with Matplotlib
1:43:00 - Creating a bar plot
1:46:09 - Customize your visualizations
1:51:04 - Creating a pie chart
1:52:14 - Fin