Data Statistics with Full Stack Python

Table of Contents

Chapter 1 : Python Fundamentals

Installation of Python and Anaconda

Python Introduction

Variables in Python

Numeric Operations in Python

Logical Operations

If else Loop

for while Loop

Functions

String Part1

String Part2

List Part1

List Part2

List Part3

List Part4

Tuples

Sets

Dictionaries

Comprehensions

Chapter 2 : Numpy

Introduction

Numpy Operations Part1

Numpy Operations Part2

Chapter 3 : Pandas

Introduction

Series

DataFrame

Operations Part1

Operations Part2

Indexes

loc and iloc

Reading CSV

Merging Part 1

groupby

Merging Part2

Pivot Table

Chapter 4 : Some Fun With Maths

Linear Algebra: Vectors

Linear Algebra: Matrix Part1

Linear Algebra: Matrix Part2

Linear Algebra: Going From 2D to nD Part1

Linear Algebra: 2D to nD Part2

Chapter 5 : Inferential Statistics

Inferential Statistics

Probability Theory

Probability Distribution

Expected Values Part1

Expected Values Part2

Without Experiment

Binomial Distribution

Commulative Distribution

PDF

Normal Distribution

z Score

Sampling

Sampling Distribution

Central Limit Theorem

Confidence Interval Part1

Confidence Interval Part2

Chapter 6 : Hypothesis Testing

Introduction

NULL and Alternate Hypothesis

Examples

One/Two Tailed Tests

Critical Value Method

z Table

Examples

More Examples

p Value

Types of Error

t- distribution Part1

t- distribution Part2

Chapter 7 : Data Visualization

Matplotlib

Seaborn

Case Study

Seaborn on Time Series Data

Chapter 8 : Exploratory Data Analysis

Introduction

Data Sourcing and Cleaning part1

Data Sourcing and Cleaning part2

Data Sourcing and Cleaning part3

Data Sourcing and Cleaning part4

Data Sourcing and Cleaning part5

Data Sourcing and Cleaning part6

Data Cleaning part1

Data Cleaning part2

Univariate Analysis Part1

Univariate Analysis Part2

Segmented Analysis

Bivariate Analysis

Derived Columns

Chapter 9 : Simple Linear Regression

Installing Anaconda using Jupyter Notebook

Introduction to Machine Learning

Types of Machine Learning

Introduction to Linear Regression (LR)

How LR Works?

Some Fun With Maths Behind LR

R Square

LR Case Study Part1

LR Case Study Part2

LR Case Study Part3

Residual Square Error (RSE)

Chapter 10 : Real World Problem - Investment Requirement Analysis for a Company

Investment Project Brief

Investment Project_Data Cleaning Part 1

Investment Project_Data Cleaning - Part 2

Investment Project_Funding_Country_Sector Analysis Part 1

Investment Project_Funding_Country_Sector Analysis Part 2

Chapter 11 : Loan Analysis Project

Problem Statement

Lending Club Default Analysis - Data Understanding and Data Cleaning

Data Analysis - Univariate Bivariate Analysis

Segmented Univariate Analysis