Learn Python Libraries For Data Analysis & Data manipulation

Description

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 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

Section 5:Handling Missing Data

Lecture 17:Handdling Missing Data in Dataframes - Fillna Method

Lecture 18:Handdling Missing Data in Dataframes - Fillna Method Continued

Lecture 19:Interpolation in Dataframes - Handling Missing Data

Lecture 20:Replace Methodd in Dataframes - Handling Missing Data

Lecture 21:Groupby in Python Pandas on Columns with repeating values

Lecture 22:Concatenate Dataframes and visualize them

Section 6:Connecting Pandas Dataframe with MySQL Server Database

Lecture 23:How to Connect Pandas With MySQL Server Database

Lecture 24:Use of Merge Method in Python Pandas

Section 7:Reshaping DataFrames in Pandas

Lecture 25:Pivot and Pivot_Table Methods in Python Pandas

Lecture 26:Stack and Unstack Methods in Python Pandas

Lecture 27:Melt Method for Data Manipulation in Pandas

Lecture 28:Crosstab method in Python Pandas

Section 8:Working with Time Series Data in Pandas

Lecture 29:DatetimeIndex in Python Pandas - Time Series

Lecture 30:date_range() method in Python Pandas - Time Series

Lecture 31:to_datetime() Method in Python Pandas

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

Lecture 32:What is JSON

Lecture 33:What is an API ?

Lecture 34:JSON API Weather Data Analysis Project Using Python Pandas and Matplotlib

Lecture 35:Stock Price Data From JSON API Analysis using Python Libraries

Section 10:EDA on Titanic Dataset from Scratch

Lecture 36:Exploratory Data Analysis on Titanic Dataset - Pie Chart and Drop

Lecture 37:Correlation Matrix or Heatmap using Seaborn EDA on Titanic Dataset

Lecture 38:Analysis of Parch and Sibsp Columns in Titanic Dataset - 3 Graphs Side By Side

Lecture 39:Histogram Plot and Kernel Density Estimation Using Python

Section 11:Restaurant Tips Dataset

Lecture 40:Scatter Plot using Python Libraries on Tips Dataset

What You Will 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

Who Should Attend!

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

TAKE THIS COURSE