Learn Python Libraries For Data Analysis & Data Manipulation

Learn Python Pandas, Matplotlib & Seaborn. Read CSV, Excel, SQL, JSON, HTML etc. Datasets.

What you'll learn
Python Pandas Library and Its Methods
Reading Data from Sources like CSV, Excel, Html, Json, Json API, Dictionary, etc, using Python Pandas
Handling Missing Data in Datasets
Working with TIme Series Datasets
Use of Matplotlib Library For Plotting Graphs like Line Graph, Bar Graph, Histogram, Pie Chart etc.
Use of Seaborn Library For Plotting Graphs like Line , Bar, Distplot, Catplot, Swarmplot etc.
Exploratory Data Analysis on Titanic Dataset
Exploratory Data Analysis on GOT Dataset
Exploratory Data Analysis on Historial Stock Data ( From JSON API)
Exploratory Data Analysis on Restaruant Tips Dataset
Requirements
Basic Knowledge of Python
Knows how to install applications on computer
Description
Lecture 2:Introduction to Python PandasLecture 3:How to Install Python Pandas on ComputerLecture 4:Data Structures in Python Pandas Section 2:Pandas SeriesLecture 5:How to Create Pandas Series from ScratchLecture 6:How to Create Pandas Series Using Ndarray and Dictionary Section 3:Pandas DataframesLecture 7:Creating Your First DataframeLecture 8:Creating a Datafram Using Python ListsLecture 9:Create an indexed DataFrame using arraysLecture 10:Getting Data of a Row or Multiple Rows in Pandas DataframeLecture 11:Basic Operations on Pandas Dataframes - Using Some Methods and AttributesLecture 12:Setting and Resetting Index of a DataframeLecture 13:How to Locate Values On the basis of Index Name Section 4:Reading CSV Files - With Exploratory Data Analysis on DatasetLecture 14:Reading CSV Files EDA On GOT Dataset Part 1Lecture 15:Reading CSV Files EDA On GOT Dataset Part 2Lecture 16:Read Excel OR Csv File and Write to an Excel Or CSV File Section 5:Handling Missing DataLecture 17:Handdling Missing Data in Dataframes - Fillna MethodLecture 18:Handdling Missing Data in Dataframes - Fillna Method ContinuedLecture 19:Interpolation in Dataframes - Handling Missing DataLecture 20:Replace Methodd in Dataframes - Handling Missing DataLecture 21:Groupby in Python Pandas on Columns with repeating valuesLecture 22:Concatenate Dataframes and visualize them Section 6:Connecting Pandas Dataframe with MySQL Server DatabaseLecture 23:How to Connect Pandas With MySQL Server DatabaseLecture 24:Use of Merge Method in Python Pandas Section 7:Reshaping DataFrames in PandasLecture 25:Pivot and Pivot_Table Methods in Python PandasLecture 26:Stack and Unstack Methods in Python PandasLecture 27:Melt Method for Data Manipulation in PandasLecture 28:Crosstab method in Python Pandas Section 8:Working with Time Series Data in PandasLecture 29:DatetimeIndex in Python Pandas - Time SeriesLecture 30:date_range() method in Python Pandas - Time SeriesLecture 31:to_datetime() Method in Python Pandas Section 9:Working with JSON Data Using JSON Module and Pandas ModuleLecture 32:What is JSONLecture 33:What is an API ?Lecture 34:JSON API Weather Data Analysis Project Using Python Pandas and MatplotlibLecture 35:Stock Price Data From JSON API Analysis using Python Libraries Section 10:EDA on Titanic Dataset from ScratchLecture 36:Exploratory Data Analysis on Titanic Dataset - Pie Chart and DropLecture 37:Correlation Matrix or Heatmap using Seaborn EDA on Titanic DatasetLecture 38:Analysis of Parch and Sibsp Columns in Titanic Dataset - 3 Graphs Side By SideLecture 39:Histogram Plot and Kernel Density Estimation Using Python Section 11:Restaurant Tips DatasetLecture 40:Scatter Plot using Python Libraries on Tips Dataset

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Introduction to Python Pandas

Lecture 3 How to Install Python Pandas on Computer

Lecture 4 Data Structures in Python Pandas

Section 2: Pandas Series

Lecture 5 How to Create Pandas Series from Scratch

Lecture 6 How to Create Pandas Series Using Ndarray and Dictionary

Section 3: Pandas Dataframes

Lecture 7 Creating Your First Dataframe

Lecture 8 Creating a Datafram Using Python Lists

Lecture 9 Create an indexed DataFrame using arrays

Lecture 10 Getting Data of a Row or Multiple Rows in Pandas Dataframe

Lecture 11 Basic Operations on Pandas Dataframes - Using Some Methods and Attributes

Lecture 12 Setting and Resetting Index of a Dataframe

Lecture 13 How to Locate Values On the basis of Index Name

Section 4: Reading CSV Files - With Exploratory Data Analysis on GOT Dataset

Lecture 14 Reading CSV Files EDA On GOT Dataset Part 1

Lecture 15 Reading CSV Files EDA On GOT Dataset Part 2

Lecture 16 Read Excel OR Csv File and Write to an Excel Or CSV File

Lecture 17 EDA on GOT Data Part 3 - Grouped Bar Chart

Lecture 18 What is a Box Plot or Box Whisker Plot ?

Section 5: Handling Missing Data

Lecture 19 Handdling Missing Data in Dataframes - Fillna Method

Lecture 20 Handdling Missing Data in Dataframes - Fillna Method Continued

Lecture 21 Interpolation in Dataframes - Handling Missing Data

Lecture 22 Replace Methodd in Dataframes - Handling Missing Data

Lecture 23 Groupby in Python Pandas on Columns with repeating values

Lecture 24 Concatenate Dataframes and visualize them

Section 6: Connecting Pandas Dataframe with MySQL Server Database

Lecture 25 How to Connect Pandas With MySQL Server Database

Lecture 26 Use of Merge Method in Python Pandas

Section 7: Reshaping DataFrames in Pandas

Lecture 27 Pivot and Pivot_Table Methods in Python Pandas

Lecture 28 Stack and Unstack Methods in Python Pandas

Lecture 29 Melt Method for Data Manipulation in Pandas

Lecture 30 Crosstab method in Python Pandas

Section 8: Working with Time Series Data in Pandas

Lecture 31 DatetimeIndex in Python Pandas - Time Series

Lecture 32 date_range() method in Python Pandas - Time Series

Lecture 33 to_datetime() Method in Python Pandas

Section 9: Working with JSON Data Using JSON Module and Pandas Module

Lecture 34 What is JSON

Lecture 35 What is an API ?

Lecture 36 JSON API Weather Data Analysis Project Using Python Pandas and Matplotlib

Lecture 37 Stock Price Data From JSON API Analysis using Python Libraries

Section 10: EDA on Titanic Dataset from Scratch

Lecture 38 Exploratory Data Analysis on Titanic Dataset - Pie Chart and Drop

Lecture 39 Correlation Matrix or Heatmap using Seaborn EDA on Titanic Dataset

Lecture 40 Analysis of Parch and Sibsp Columns in Titanic Dataset - 3 Graphs Side By Side

Lecture 41 Histogram Plot and Kernel Density Estimation Using Python

Section 11: Restaurant Tips Dataset

Lecture 42 Scatter Plot using Python Libraries on Tips Dataset

Lecture 43 FacetGrid Plot in Seaborn Library on Tips Dataset

Lecture 44 3D Plot Using MatplotLib in Python - Introduction

Section 12: Graphical Analysis on Misc Datasets

Lecture 45 Stacked Bar Chart Plot Using Python Matplotlib on Cricket Series Data

Lecture 46 Code For Grouped Bar Chart Using Matplotlib

Lecture 47 Lmplot - Regression and Scatter - On Flights Dataset

Section 13: Read_html() Method in Pandas

Lecture 48 Read_html in Python Pandas Reading Table from a website

Lecture 49 Creating HTML Table and Reading Data from Local Html File

Section 14: Iris Dataset

Lecture 50 Seaborn Pairplot Example on Iris Dataset

Beginner Python Developers curious about Data Science,College or School Students who want to Learn Data Analysis