Python Data Analysis and Visualization Full Course for Beginners
This course will give you the resources to learn python and effectively use it analyze and visualize data! Start your career in Data Science!
Learn how to do Exploratory Data Analysis, Data Insight, Data Manipulation and Data Visualization with Python
You'll get a full understanding of how to program with Python and how to use it in conjunction with scientific computing modules and libraries to analyze data.
By the end of this course you will:
Have an understanding of how to program in Python.
Know how to create and manipulate arrays using Numpy and Python.
Know how to use Pandas to create and analyze data sets.
Know how to use Matplotlib and Seaborn libraries to create beautiful data visualization.
Grasp the theoretical and practical concepts parallel
Have hands-on experience on KFC data set
Have an amazing portfolio of example python data analysis projects!
With 30+ lectures and over 10+ labs, you will be excellently prepared for a future in data science!
TIMELINE:
Course Introduction 00:00:00 - 00:02:34
Section 1: UNBOXIG DATA ANALYSIS AND PYTHON
What is Data Analysis and Data Visualization? 00:02:35 - 00:12:40
Why Python and Data Analysis? 00:12:41 - 00:14:21
What is Data Wrangling and Data Cleaning? 00:14:22 - 00:15:58
SECTION 2: SETTING UP PYTHON ENVIRONMENT
Installing Python on Mac 00:15:59 - 00:19:39
Installing Python on Windows 00:19:40 - 00:24:35
Installing Anaconda on Windows. 00:24:35 - 00:27:43
Installing Python on Linux 00:27:44 - 00:33:29
SECTION 3: PYTHON PREIMER
Syntax in Python 00:33:30 - 00:36:45
Variables in Python 00:36:46 - 00:43:23
Data Types in Python 00:43:24 - 00:47:10
Comments in Python 00:47:11 - 00:50:30
Exception Handling in Python 00:50:31 - 01:02:36
SECTION 4: WORKING WITH DATA STRUCTURES
Standard Data Structures 01:02:36 - 01:03-23
List 01:03:24 - 01:17:56
Tuple 01:17:58 - 01:29:51
Dictionary 01:29:52 - 01:40:00
Set 01:40:02 - 01:53:35
Section 5: Data Formats and Sources
Data Formats 01:53:36 - 01:56:42
Importing Data Sets From Facebook 01:56:43 - 02:07:42
Importing Datasets from Public Sources 02:07:45 - 02:19:47
Section 6: Data Preparation
Introduction to Numpy 02:19:49 - 02:22:11
Data Types 02:22:12 - 02:24:52
Arrays 02:24:53 - 02:28:19
Array Functions 02:28:20 - 02:33:20
Operations on Arrays 02:33:21 - 02:37-44
LAB: Numpy 02:37:45 - 02:49:04
Section 7: Data Preparation (PANDAS)
Data Preparation 02:49:05 - 02:55:10
Loading and Saving Data 02:55:11 - 02:58:36
Pandas Functions 02:58:37 - 03:00:20
Regular Expression 03:00:22 - 03:04:09
LAB: Pandas 03:04:10 - 03:26:04
LAB: Regular Expression 03:26:05 - 03:35:45
Section 8: Exploratory Data Analysis 03:35:46 - 4:32:30
Section 9: Data Visualization 4:32:31 - 5:28:47
Capstone Project: KFC 5:28:48
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