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What you'll learn?
- What is Python Pandas library or module & how to use its methods.
- How to use pandas in Data Analysis And data Science.
- Use Python BS4 & Pandas to Scrape a web-page, Analyze and visualize The Scraped Data.
- Use Python to load Postgres Data Output file.
- Use Python Pandas to Analyze and visualize Postgres Data Output.
- Use Python to visualize Postgres Data Output and get your Conclusion about Data.
Course Overview
The most important part of data science is understanding the data that is available to data scientists. You will only be able to achieve the best outcomes if you have the correct knowledge of data and the appropriate data for the task at hand. The analysis, Visualization, and manipulation of data are all very important in Data Science.
Everything about machine learning and data science is made exceedingly simple with Python. We may easily achieve any desired action by utilizing some of the top libraries available in Python. Pandas is one such package that allows us to examine and manipulate data in order to reduce the complexity and speed up the problem-solving process.
One of the best features available in Python for data analysis operations is the Pandas library. You are capable of doing a wide range of jobs with ease. In this course, we'll look at the various sorts of operations that every data scientist must employ in order to complete a project with the least amount of resources while reaching the maximum level of efficiency.
Pre-requisites
- Computer and internet.
- No primer programming experience needed for this course.
Target Audience
- Are you want to learn more about Python Pandas library Methods & Functions?
- Are you want to learn more about Data Analysis using Python Pandas library?
- Are you want to learn more about Python + PostgreSQL?
- Use Python bs4 & Pandas to Scrape a webpage, Analyze and visualize The Scraped Data.
Curriculum 43 Lectures 06:04:56
-
Section 1 : Introduction to this Course
-
Section 2 : Introduction to Python
- Lecture 1 :
- Python2 VS Python3
- Lecture 2 :
- Understanding Data Types in Python
-
Section 3 : Python refresher
- Lecture 1 :
- Variables, Operators and Data Types in Python
- Lecture 2 :
- String Functions in Python
- Lecture 3 :
- Control Flow VS Loops
- Lecture 4 :
- Data Structures in Python
- Lecture 5 :
- Error Handling in Python
- Lecture 6 :
- Functions in Python
- Lecture 7 :
- Files and Modules in Python
-
Section 4 : Python OOP
- Lecture 1 :
- Creating Simple Class
- Lecture 2 :
- Overviewing Constructor
- Lecture 3 :
- Learning How to creating Dunder Methods
- Lecture 4 :
- Learning about Inheritance
- Lecture 5 :
- Knowing What is the Encapsulation
- Lecture 6 :
- Learning also about Multiple Inheritance
- Lecture 7 :
- Knowing What is the Overriding
- Lecture 8 :
- Learning about Decorators
- Lecture 9 :
- Learning How to use Build in Decorators
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Section 5 : Project 1 Color Choices
- Lecture 1 :
- Project Walkthrough
- Lecture 2 :
- Project help
- Lecture 3 :
- 3- Project solution
-
Section 6 : Project 2 hangman
- Lecture 1 :
- Hangman Walkthrough
- Lecture 2 :
- Hangman Helpful Notes
- Lecture 3 :
- Project Solution Part 1
- Lecture 4 :
- Project Solution Part 2
-
Section 7 : Project 3 X-O Game
- Lecture 1 :
- X-O project part 1
- Lecture 2 :
- X-O project part 2
- Lecture 3 :
- X-O project part 3
-
Section 8 : Project 4_ XTwitter ChatBot
- Lecture 1 :
- TwitterChatBot Part 1
- Lecture 2 :
- Twitter ChaBot Part 2
- Lecture 3 :
- Twitter ChatBot Part3
-
Section 9 : Project 5 Data Analysis _ Data Visualization of the Scraped Data
- Lecture 1 :
- visualize scraped data
-
Section 10 : Project 4 Scraping The Web Using Python
- Lecture 1 :
- How to Scrape a website part 1
- Lecture 2 :
- How to Scrape a website part 2
- Lecture 3 :
- Using Pandas and LXML Python Modules to scrape a webpage
-
Section 11 : Project 6 Saving the Scraped data to a newly created Database
- Lecture 1 :
- Saving the Scraped data to a newly created Database
-
Section 12 : Project 1 Google Play Store Data Analysis
- Lecture 1 :
- Exploratory Data Analysis (EDA) of Google App Store Data
- Lecture 2 :
- Data Visualization Techniques ok
- Lecture 3 :
- Data Visualization Techniques
- Lecture 4 :
- Statistical Analysis and Hypothesis Testing.
- Lecture 5 :
- Data Storytelling.
- Lecture 6 :
- Conclusion.
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Instructor
6965 Course Views
13 Courses
Hello there! With over 350,000 happy students enrolled in my courses, I'm thrilled to be sharing my programming and data science expertise with you.
As a programmer and data scientist, I've mastered several programming languages, including Python, SQL, JavaScript, R Programming, as well as tools like Excel, Tableau, Jupyter Notebook, Apache Cassandra, Apache Spark, Apache Airflow, Apache Kafka, AWS, and R Studio. I'm passionate about teaching and sharing my knowledge with the community.
When I'm not coding, you can usually find me hiking or reading a good book. I believe that lifelong learning is essential for personal development, and my courses are designed to encourage students to continue learning outside of formal education.
I update my courses every month to add new sections based on your feedback and requests. So don't wait – enroll in my courses now and start your journey towards mastering programming, web development, data science, data Engineering and Machine Learning!
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