Data Analyst – Thinkersklub

About Course

Complete Data Analyst Training: Python, NumPy, Pandas, Data Collection, Preprocessing, Data Types, Data Visualization

Course Content

01 – Introduction to the Course
Introduction to the Course

001 A Practical Example – What Will You Learn in This Course

04:47
002 What Does the Course Cover

05:37
003 Download All Resources
004 FAQ

02 – Introduction to Data Analytics
Introduction to Data Analytics

03 – Setting up the Environment
Setting up the Environment

001 Introduction

01:24
002 Programming Explained in a Few Minutes

05:04
003 Programming Explained in a Few Minutes
004 Jupyter Introduction

03:29
005 Jupyter Installing Anaconda

04:00
006 Jupyter Intro to Using Jupyter

03:11
007 Jupyter Working with Notebook Files

06:09
008 Jupyter Using Shortcuts

03:07
009 Jupyter Handling Error Messages

05:53
010 Jupyter Restarting the Kernel

02:18
011 Jupyter – Introduction

04 – Python Basics
Python Basics

05 – Fundamentals for Coding in Python
Fundamentals for Coding in Python

06 – Mathematics for Python
Mathematics for Python

001 What Is а Matrix

03:37
002 Scalars and Vectors

02:58
003 Linear Algebra and Geometry

03:06
004 Arrays in Python

05:09
005 What Is a Tensor

03:00
006 Adding and Subtracting Matrices

03:36
007 Errors When Adding Matrices

02:01
008 Transpose

05:13
009 Dot Product of Vectors

03:48
010 Dot Product of Matrices

08:23
011 Why is Linear Algebra Useful

10:10

07 – NumPy Basics
NumPy Basics

08 – Pandas – Basics
Pandas - Basics

001 Introduction to the pandas Library

05:41
002 Installing and Running pandas

05:57
003 Installing and Running pandas – Exercise #1
004 A Note on Completing the Upcoming Coding Exercises
005 Installing and Running pandas – Exercise #2
006 Introduction to pandas Series

08:41
007 Introduction to pandas Series – Exercise #1
008 Introduction to pandas Series – Exercise #2
009 Introduction to pandas Series – Exercise #3
010 Introduction to pandas Series – Exercise #4
011 Introduction to pandas Series – Exercise #5
012 Introduction to pandas Series – Exercise #6
013 Introduction to pandas Series – Exercise #7
014 Introduction to pandas Series – Exercise #8
015 Introduction to pandas Series – Exercise #9
016 Introduction to pandas Series – Exercise #10
017 Working with Attributes in Python

05:22
018 Working with Attributes in Python – Exercise #1
019 Working with Attributes in Python – Exercise #2
020 Working with Attributes in Python – Exercise #3
021 Working with Attributes in Python – Exercise #4
022 Working with Attributes in Python – Exercise #5
023 Working with Attributes in Python – Exercise #6
024 Working with Attributes in Python – Exercise #7
025 Using an Index in pandas

04:01
026 Using an Index in pandas – Exercise #1
027 Using an Index in pandas – Exercise #2
028 Using an Index in pandas – Exercise #3
029 Using an Index in pandas – Exercise #4
030 Using an Index in pandas – Exercise #5
031 Label based vs Position based Indexing

04:31
032 Label-based vs Position-based Indexing – Exercise #1
033 Label-based vs Position-based Indexing – Exercise #2
034 More on Working with Indices in Python

05:37
035 More on Working with Indices in Python – Exercise #3
036 More on Working with Indices in Python – Exercise #4
037 More on Working with Indices in Python – Exercise #5
038 Using Methods in Python Part I

04:55
039 Using Methods in Python Part II

02:36
040 Using Methods in Python – Exercise #1
041 Using Methods in Python – Exercise #2
042 Parameters vs Arguments

04:35
043 Parameters vs Arguments – Exercise #1
044 Parameters vs Arguments – Exercise #2
045 The pandas Documentation

09:54
046 Introduction to pandas DataFrames

05:23
047 Creating DataFrames from Scratch Part I

05:56
048 Creating DataFrames from Scratch – Exercise #1
049 Creating DataFrames from Scratch – Exercise #2
050 Creating DataFrames from Scratch Part II

05:03
051 Creating DataFrames from Scratch – Exercise #3
052 Creating DataFrames from Scratch – Exercise #4
053 Creating DataFrames from Scratch – Exercise #5
054 Additional Notes on Using DataFrames

01:58
055 pandas Basics – Conclusion

09 – Working with Text Files
Working with Text Files

001 Working with Files in Python An Introduction

03:47
002 File vs File Object, Read vs Parse

02:53
003 Structured vs Semi Structured and Unstructured Data

03:10
004 Data Connectivity through Text Files

03:07
005 Principles of Importing Data in Python

04:50
006 More on Text Files txt vs csv

04:34
007 Fixed width Files

01:26
008 Common Naming Conventions Used in Programming

03:50
009 Importing Text Files in Python open

09:02
010 Importing Text Files in Python ( open() ) – Exercise #1
011 Importing Text Files in Python ( open() ) – Exercise #2
012 Importing Text Files in Python with open

04:54
013 Importing Text Files in Python ( with open() ) – Exercise #1
014 Importing Text Files in Python ( with open() ) – Exercise #2
015 Importing Text Files in Python ( with open() ) – Exercise #3
016 Importing Text Files in Python ( with open() ) – Exercise #4
017 Importing Text Files in Python ( with open() ) – Exercise #5
018 Importing csv Files with pandas Part I

05:37
019 Importing csv Files with pandas Part II

02:37
020 Importing csv Files with pandas Part III

05:59
021 Importing Data with the index col Parameter

02:36
022 Importing Data with NumPy loadtxt vs genfromtxt

10:46
023 Importing Data with NumPy Partial Cleaning While Importing

07:22
024 Importing json Files

05:16
025 Prelude to Working with Excel Files in Python

03:41
026 Working with Excel Data the xlsx Format

01:56
027 Importing Data with NumPy – Exercise
028 An Important Exercise on Importing Data in Python

05:45
029 Importing Data with the pandas’ Squeeze Method

03:23
030 A Note on Importing Files in Jupyter

03:11
031 Saving Your Data with pandas

03:12
032 Saving Your Data with NumPy np save

05:24
033 Saving Your Data with NumPy np savez

05:13
034 Saving Your Data with NumPy np savetxt

03:59
035 Saving Your Data with NumPy – Exercise
036 Working with Text Files Conclusion

00:42

10 – Working with Text Data
Working with Text Data

11 – Must-Know Python Tools
Must-Know Python Tools

12 – Data GatheringData Collection
Data GatheringData Collection

13 – APIs (POST requests are not needed for this course)
APIs (POST requests are not needed for this course)

14 – Data Cleaning and Data Preprocessing
Data Cleaning and Data Preprocessing

15 – pandas Series
15 - pandas Series

16 – pandas DataFrames
16 - pandas DataFrames

17 – NumPy Fundamentals
NumPy Fundamentals

18 – NumPy DataTypes
NumPy DataTypes

19 – Working with Arrays
Working with Arrays

20 – Generating Data with NumPy
Generating Data with NumPy

21 – Statistics with NumPy
21 - Statistics with NumPy

22 – NumPy – Preprocessing
22 - NumPy - Preprocessing

23 – A Loan Data Example with NumPy
A Loan Data Example with NumPy

24 – The Absenteeism Exercise – Introduction
The Absenteeism Exercise - Introduction

25 – Solution to the Absenteeism Exercise
Solution to the Absenteeism Exercise

26 – Data Visualization
Data Visualization

27 – Conclusion
Conclusion

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About Course

Course Content

01 – Introduction to the Course Introduction to the Course

001 A Practical Example – What Will You Learn in This Course

002 What Does the Course Cover

003 Download All Resources

004 FAQ

02 – Introduction to Data Analytics Introduction to Data Analytics

001 Introduction to the World of Business and Data

002 Relevant Terms Explained

003 Data Analyst Compared to Other Data Jobs

004 Data Analyst Job Description

005 Why Python

03 – Setting up the Environment Setting up the Environment

001 Introduction

002 Programming Explained in a Few Minutes

003 Programming Explained in a Few Minutes

004 Jupyter Introduction

005 Jupyter Installing Anaconda

006 Jupyter Intro to Using Jupyter

007 Jupyter Working with Notebook Files

008 Jupyter Using Shortcuts

009 Jupyter Handling Error Messages

010 Jupyter Restarting the Kernel

011 Jupyter – Introduction

04 – Python Basics Python Basics

Python Basics

05 – Fundamentals for Coding in Python Fundamentals for Coding in Python

001 Object Oriented Programming OOP

002 Modules, Packages, and the Python Standard Library

003 Importing Modules

004 Introduction to Using NumPy and pandas

005 What is Software Documentation

006 The Python Documentation

06 – Mathematics for Python Mathematics for Python

001 What Is а Matrix

002 Scalars and Vectors

003 Linear Algebra and Geometry

004 Arrays in Python

005 What Is a Tensor

006 Adding and Subtracting Matrices

007 Errors When Adding Matrices

008 Transpose

009 Dot Product of Vectors

010 Dot Product of Matrices

011 Why is Linear Algebra Useful

07 – NumPy Basics NumPy Basics

001 The NumPy Package and Why We Use It

002 InstallingUpgrading NumPy

003 Ndarray

004 The NumPy Documentation

005 NumPy Basics – Exercise

08 – Pandas – Basics Pandas - Basics

001 Introduction to the pandas Library

002 Installing and Running pandas

003 Installing and Running pandas – Exercise #1

004 A Note on Completing the Upcoming Coding Exercises

005 Installing and Running pandas – Exercise #2

006 Introduction to pandas Series

007 Introduction to pandas Series – Exercise #1

008 Introduction to pandas Series – Exercise #2

009 Introduction to pandas Series – Exercise #3

010 Introduction to pandas Series – Exercise #4

011 Introduction to pandas Series – Exercise #5

012 Introduction to pandas Series – Exercise #6

013 Introduction to pandas Series – Exercise #7

014 Introduction to pandas Series – Exercise #8

015 Introduction to pandas Series – Exercise #9

016 Introduction to pandas Series – Exercise #10

017 Working with Attributes in Python

018 Working with Attributes in Python – Exercise #1

019 Working with Attributes in Python – Exercise #2

020 Working with Attributes in Python – Exercise #3

021 Working with Attributes in Python – Exercise #4

022 Working with Attributes in Python – Exercise #5

023 Working with Attributes in Python – Exercise #6

024 Working with Attributes in Python – Exercise #7

025 Using an Index in pandas

026 Using an Index in pandas – Exercise #1

027 Using an Index in pandas – Exercise #2

01 – Introduction to the Course
Introduction to the Course

02 – Introduction to Data Analytics
Introduction to Data Analytics

03 – Setting up the Environment
Setting up the Environment

04 – Python Basics
Python Basics

05 – Fundamentals for Coding in Python
Fundamentals for Coding in Python

06 – Mathematics for Python
Mathematics for Python

07 – NumPy Basics
NumPy Basics

08 – Pandas – Basics
Pandas - Basics

09 – Working with Text Files
Working with Text Files

10 – Working with Text Data
Working with Text Data

11 – Must-Know Python Tools
Must-Know Python Tools