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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 |
| Updated and Published: | August 14, 2022 |
Requirements
- Basic Knowledge of Python
- Knows how to install applications 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 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
Who this course is for:
- Beginner Python Developers curious about Data Science
- College or School Students who want to Learn Data Analysis
DOWNLOAD LINK: Learn Python Libraries For Data Analysis & Data Manipulation
Learn_Python_Libraries_For_Data_Analysis.part1.rar – 4.0 GB
Learn_Python_Libraries_For_Data_Analysis.part2.rar – 3.9 GB
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