100% Discount || The Pandas Bootcamp | Data Analysis with Pandas Python3

Introduction to The Pandas Bootcamp | Data Analysis with Pandas Python3

The “Introduction to The Pandas Bootcamp | Data Analysis with Pandas Python3” course is designed for anyone who wants to learn how to use Pandas, the popular data manipulation library for Python.

This course covers a wide range of topics, from the basics of Pandas installation and data structures to more advanced topics such as window functions and visualization.

Whether you are a beginner or an experienced programmer, this course will provide you with a comprehensive understanding of how to use Pandas to analyze and manipulate data efficiently.

Through practical programming examples, you will learn how to perform data cleaning and manipulation, aggregation, and grouping, as well as how to work with different data formats such as CSV, Excel, and JSON. By the end of the course, you will have gained the knowledge and skills necessary to work with large datasets and perform complex data analysis tasks using Pandas.

********** Instructors Experiences and Education: **********

Faisal Zamir is an experienced programmer and an expert in the field of computer science. He holds a Master’s degree in Computer Science and has over 7 years of experience working in schools, colleges, and university. Faisal is a highly skilled instructor who is passionate about teaching and mentoring students in the field of computer science.

As a programmer, Faisal has worked on various projects and has experience in multiple programming languages, including PHP, Java, and Python.

He has also worked on projects involving web development, software engineering, and database management. This broad range of experience has allowed Faisal to develop a deep understanding of the fundamentals of programming and the ability to teach complex concepts in an easy-to-understand manner.

As an instructor, Faisal has a proven track record of success. He has taught students of all levels, from beginners to advanced, and has a passion for helping students achieve their goals.

Faisal has a unique teaching style that combines theory with practical examples, which allows students to apply what they have learned in real-world scenarios.

Overall, Faisal Zamir is a skilled programmer and a talented instructor who is dedicated to helping students achieve their goals in the field of computer science. With his extensive experience and proven track record of success, students can trust that they are learning from an expert in the field.

What you will learn from  Course Data Analysis with Pandas Python3

1. Understand the basics of Pandas, its data structures, and how to install it.
2. Work with different types of data structures in Pandas.
3. Use descriptive and inferential statistics methods to analyze data.
4. Apply element-wise, row or column-wise, and table-wise function application on data.
5. Reindex, sort, and iterate through data using Pandas.
6. Use string methods for data cleaning and manipulation.
7. Customize display options and data types in Pandas.
8. Perform indexing and selecting operations based on labels, integers, or Boolean values.
9. Use window functions such as rolling, expanding, and ewm for data analysis.
10. Group data based on single or multiple columns, apply aggregation functions, and filter or transform data.
11. Work with categorical data, perform methods such as reorder, remove, add, and rename categories, and visualize categorical data using Pandas.
12. Visualize data using different types of plots such as line, bar, histogram, scatter, box, area, and heatmap.
13. Read and write data in different formats such as CSV, Excel, and JSON using Pandas.
14. Work with sparse data and understand its features.

************ Outlines for Pandas Course for Data Science ************

Chapter 01

• Introduction
• What is Pandas
• Why need of Pandas
• What we can do with Pandas
• Pandas Installation
• Pandas Basic Program

Chapter 02

• Data Structures
• Types of Data Structure

Chapter 03

• Series
• Series different OperationS
• Series Attributes
• Series methods
• DataFrame
• Panel

Chapter 04

• DataFrame
• DataFrame different OperationS
• DataFrame Attributes
• DataFrame methods
• Panel

Chapter 05

• Descriptive Statistics
• Descriptive Statistics Methods & Programming Examples
• Inferential statistics functions

Chapter 06

• Function Application
• Element-wise
• Row or Column-wise
• Table-wise

Chapter 07

• Reindexing
• Reindexing Method with Programming Examples
• Iteration
• Iteration Method with Programming Examples
• Sorting
• Sorting Method with Programming Examples

Chapter 08

• String Methods
• lower()
• upper()
• title()
• capitalize()
• swapcase()
• strip()
• lstrip()
• rstrip()
• split()
• rsplit()
• join()
• replace()
• contains()
• startswith()
• endswith()
• find()
• rfind()
• count()
• len()