Udemy - Pandas Python Programming Language Library From Scratch A-Z

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[ DevCourseWeb.com ] Udemy - Pandas Python Programming Language Library From Scratch A-Z
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Python Installations (Anaconda Navigator, Jupyter Notebook, Jupyter Lab)
    • 1. Installing Anaconda Distribution for Windows.mp4 (122.6 MB)
    • 2. Installing Anaconda Distribution for MacOs.mp4 (57.9 MB)
    • 3. Installing Anaconda Distribution for Linux.mp4 (119.8 MB)
    10. Pivot Tables in Pandas Library
    • 1. Examining the Data Set 3.mp4 (35.6 MB)
    • 2. Pivot Tables in Pandas Library.mp4 (50.0 MB)
    • 3. quiz.html (0.2 KB)
    11. File Operations in Pandas Library
    • 1. Accessing and Making Files Available.mp4 (32.3 MB)
    • 2. Data Entry with Csv and Txt Files.mp4 (59.3 MB)
    • 3. Data Entry with Excel Files.mp4 (19.8 MB)
    • 4. Outputting as an CSV Extension.mp4 (32.8 MB)
    • 5. Outputting as an Excel File.mp4 (18.1 MB)
    • 6. quiz.html (0.2 KB)
    12. Extra
    • 1. Pandas Python Programming Language Library From Scratch A-Z™.html (0.3 KB)
    2. Pandas Library Introduction
    • 1. Introduction to Pandas Library.mp4 (32.3 MB)
    • 2. Pandas Project Files Link.html (0.2 KB)
    • 3. quiz.html (0.2 KB)
    3. Series Structures in the Pandas Library
    • 1. Creating a Pandas Series with a List.mp4 (36.3 MB)
    • 2. Creating a Pandas Series with a Dictionary.mp4 (16.8 MB)
    • 3. Creating Pandas Series with NumPy Array.mp4 (11.0 MB)
    • 4. Object Types in Series.mp4 (18.0 MB)
    • 5. Examining the Primary Features of the Pandas Seri.mp4 (17.4 MB)
    • 6. Most Applied Methods on Pandas Series.mp4 (44.1 MB)
    • 7. Indexing and Slicing Pandas Series.mp4 (26.9 MB)
    • 8. quiz.html (0.2 KB)
    4. DataFrame Structures in Pandas Library
    • 1. Creating Pandas DataFrame with List.mp4 (21.1 MB)
    • 2. Creating Pandas DataFrame with NumPy Array.mp4 (11.2 MB)
    • 3. Creating Pandas DataFrame with Dictionary.mp4 (14.7 MB)
    • 4. Examining the Properties of Pandas DataFrames.mp4 (23.9 MB)
    • 5. quiz.html (0.2 KB)
    5. Element Selection Operations in DataFrame Structures
    • 1. Element Selection Operations in Pandas DataFrames Lesson 1.mp4 (27.4 MB)
    • 2. Element Selection Operations in Pandas DataFrames Lesson 2.mp4 (29.4 MB)
    • 3. Top Level Element Selection in Pandas DataFramesLesson 1.mp4 (35.5 MB)
    • 4. Top Level Element Selection in Pandas DataFramesLesson 2.mp4 (29.0 MB)
    • 5. Top Level Element Selection in Pandas DataFramesLesson 3.mp4 (20.5 MB)
    • 6. Element Selection with Conditional Operations in.mp4 (42.5 MB)
    • 7. quiz.html (0.2 KB)
    6. Structural Operations on Pandas DataFrame
    • 1. Adding Columns to Pandas Data Frames.mp4 (31.1 MB)
    • 2. Removing Rows and Columns from Pandas Data frames.mp4 (14.4 MB)
    • 3. Null Values in Pandas Dataframes.mp4 (62.4 MB)
    • 4. Dropping Null Values Dropna() Function.mp4 (31.8 MB)
    • 5. Filling Null Values Fillna() Function.mp4 (47.9 MB)
    • 6. Setting Index in Pandas DataFrames.mp4 (36.4 MB)
    • 7. quiz.html (0.2 KB)
    7. Multi-Indexed DataFrame Structures
    • 1. Multi-Index and Index Hierarchy in Pandas DataFrames.mp4 (39.5 MB)
    • 2. Element Selection in Multi-Indexed DataFrames.mp4 (22.4 MB)
    • 3. Selecting Elements Using the xs() Function in Multi-Indexed DataFrames.mp4 (28.2 MB)
    • 4. quiz.html (0.2 KB)
    8. Structural Concatenation Operations in Pandas DataFrame
    • 1. Concatenating Pandas Dataframes Concat Function.mp4 (58.0 MB)
    • 2. Merge Pandas Dataframes Merge() Function Lesson 1.mp4 (51.3 MB)
    • 3. Merge Pandas Dataframes Merge() Function Lesson 2.mp4 (27.4 MB)
    • 4. Merge Pandas Dataframes Merge() Function Lesson 3.mp4 (53.8 MB)
    • 5. Merge Pandas Dataframes Merge() Function Lesson 4.mp4 (37.5 MB)
    • 6. Joining Pandas Dataframes Join() Function.mp4 (51.9 MB)
    • 7. quiz.html (0.2 KB)
    9. Functions That Can Be Applied on a DataFrame
    • 1. Loading a Dataset from the Seaborn Library.mp4 (35.0 MB)
    • 10. quiz.html (0.2 KB)
    • 2. Examining the Data Set 1.mp4 (39.2 MB)
    • 3. Aggregation Functions in Pandas DataFrames.mp4 (83.6 MB)
    • 4. Examining the Data Set 2.mp4 (42.6 MB)
    • 5. Coordinated Use of Grouping and Aggregation Functions in Pandas Dataframes.mp4 (80.9 MB)
    • 6. Advanced Aggregation Functions Aggregate() Function.mp4 (26.9 MB)
    • 7. Advanced Aggregation Functions Filter() Function.mp4 (23.0 MB)
    • 8. Advanced Aggregation Functions Transform() Function.mp4 (43.7 MB)
    • 9. Advanced Aggregation Functions Apply() Function.mp4 (38.3 MB)
    • Bonus Resources.txt (0.4 KB)

Description

Pandas Python Programming Language Library From Scratch A-Z™



https://DevCourseWeb.com

Published 10/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 54 lectures (7h 30m) | Size: 2 GB

Pandas mainly used for Python Data Analysis. Learn Pandas for Data Science, Machine Learning, Deep Learning using Python

What you'll learn
Pandas is an open source Python package that is most widely used for data science/data analysis and machine learning tasks.
Pandas is mainly used for data analysis and associated manipulation of tabular data in DataFrames.
Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
Pandas Pyhon aims to be the fundamental high-level building block for doing practical, real world data analysis in Python
Installing Anaconda Distribution for Windows
Installing Anaconda Distribution for MacOs
Installing Anaconda Distribution for Linux
Introduction to Pandas Library
Creating a Pandas Series with a List
Creating a Pandas Series with a Dictionary
Creating Pandas Series with NumPy Array
Object Types in Series
Examining the Primary Features of the Pandas Series
Most Applied Methods on Pandas Series
Indexing and Slicing Pandas Series
Creating Pandas DataFrame with List
Creating Pandas DataFrame with NumPy Array
Creating Pandas DataFrame with Dictionary
Examining the Properties of Pandas DataFrames
Element Selection Operations in Pandas DataFrames
Top Level Element Selection in Pandas DataFrames: Structure of loc and iloc
Element Selection with Conditional Operations in Pandas Data Frames
Adding Columns to Pandas Data Frames
Removing Rows and Columns from Pandas Data frames
Null Values ​​in Pandas Dataframes
Dropping Null Values: Dropna() Function
Filling Null Values: Fillna() Function
Setting Index in Pandas DataFrames
Multi-Index and Index Hierarchy in Pandas DataFrames
Element Selection in Multi-Indexed DataFrames
Selecting Elements Using the xs() Function in Multi-Indexed DataFrames
Concatenating Pandas Dataframes: Concat Function
Merge Pandas Dataframes: Merge() Function
Joining Pandas Dataframes: Join() Function
Loading a Dataset from the Seaborn Library
Aggregation Functions in Pandas DataFrames
Coordinated Use of Grouping and Aggregation Functions in Pandas Dataframes
Advanced Aggregation Functions: Aggregate() Function
Advanced Aggregation Functions: Filter() Function
Advanced Aggregation Functions: Transform() Function
Advanced Aggregation Functions: Apply() Function
Pivot Tables in Pandas Library
Data Entry with Csv and Txt Files
Data Entry with Excel Files
Outputting as an CSV Extension
Outputting as an Excel File

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Udemy - Pandas Python Programming Language Library From Scratch A-Z
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