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File Name: Learn Python Libraries For Data Analysis & Data Manipulation

Content Source: https://www.udemy.com/course/learn-python-libraries-for-data-analysis-data-manipulation/

Genre / Category: Programming

File Size : 8GB

Publisher: udemy



Requirements


  • Basic Knowledge of Python
  • Knows how to installation purposes on computer
  • 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 listed DataFrame the usage of 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 foundation 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 technique in Python Pandas

Section 8:Working with Time Series Data in Pandas

Lecture 29:DatetimeIndex in Python Pandas – Time Series

Lecture 30:date_range() approach 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 the use of 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 the usage of Seaborn EDA on Titanic Dataset

Lecture 38:Analysis of Parch and Sibsp Columns in Titanic Dataset – three Graphs Side By Side

Lecture 39:Histogram Plot and Kernel Density Estimation Using Python

Section 11:Restaurant Tips Dataset

Lecture 40:Scatter Plot the usage of Python Libraries on Tips Dataset

Who this route is for:


Beginner Python Developers curious about Data Science

College or School Students who desire to Learn Data Analysis