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Python Pandas Programming With Coding Exercises





Published 8/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 231.11 MB | Duration: 2h 14m

Master Data Analysis with Python Pandas through Hands-on Coding Exercises


What you'll learn
How to create, manipulate, and analyze data using Pandas DataFrames and Series.
Techniques for cleaning, preprocessing, and preparing data for analysis.
Methods to merge, join, and aggregate data for insightful analysis.
Practical skills in visualizing data and generating reports using Pandas.
Requirements
Basic understanding of Python programming.
Description
Unlock the full potential of Python's powerful Pandas library in this comprehensive course, Python Pandas Programming with Coding Exercises. This course is designed to help you master data analysis and manipulation with Pandas, one of the most essential tools in a data scientist's toolkit. Whether you're a beginner eager to dive into data science or an experienced programmer looking to sharpen your skills, this course provides everything you need.Why is learning Pandas necessary? In today's data-driven world, the ability to efficiently manipulate, analyze, and visualize data is crucial across various industries. Pandas is the go-to library for these tasks in Python, and mastering it opens the door to a multitude of opportunities in data science, machine learning, and beyond.Throughout the course, you'll work on coding exercises that cover a wide range of topics, including:DataFrames and Series creation and manipulationImporting and exporting data from various formats (CSV, Excel, etc.)Data cleaning and preprocessing techniquesGrouping, merging, and joining datasetsAdvanced data manipulation techniquesHandling time series dataVisualization with PandasEach exercise is designed to reinforce your understanding and build confidence in using Pandas for real-world applications. By the end of the course, you'll have the skills to tackle any data-related challenge with ease.Instructor Introduction: Faisal Zamir, a seasoned Python developer with over 7 years of teaching experience, is your guide throughout this course. Faisal's expertise in Python programming and data analysis ensures that you'll receive top-notch instruction and valuable insights.30 Days Money-Back Guarantee: We stand behind the quality of this course. If you're not satisfied, we offer a 30-day money-back guarantee, no questions asked.Certificate at the End of the Course: Upon completing the course, you'll receive a certificate that showcases your newly acquired skills in Python Pandas, a valuable addition to your professional portfolio.
Overview
Section 1: Introduction to Pandas
Lecture 1 Introduction to Pandas
Lecture 2 Lesson 01
Lecture 3 Coding Exercises with Solutions
Section 2: Data Selection and Filtering
Lecture 4 Data Selection and Filtering
Lecture 5 Lesson 02
Lecture 6 Coding Exercises with Solutions
Section 3: Data Cleaning and Preprocessing
Lecture 7 Data Cleaning and Preprocessing
Lecture 8 Lesson 03
Lecture 9 Coding Exercises with Solutions
Section 4: Data Manipulation
Lecture 10 Data Manipulation
Lecture 11 Lesson 04
Lecture 12 Coding Exercises with Solutions
Section 5: Aggregation and Grouping
Lecture 13 Aggregation and Grouping
Lecture 14 Lesson 05
Lecture 15 Coding Exercises with Solutions
Section 6: Merging and Joining Data
Lecture 16 Merging and Joining Data
Lecture 17 Lesson 06
Lecture 18 Coding Exercises with Solutions
Section 7: Pivoting and Reshaping Data
Lecture 19 Pivoting and Reshaping Data
Lecture 20 Lesson 07
Lecture 21 Coding Exercises with Solutions
Section 8: Time Series Analysis
Lecture 22 Time Series Analysis
Lecture 23 Lesson 08
Lecture 24 Coding Exercises with Solutions
Section 9: Advanced Data Operations
Lecture 25 Advanced Data Operations
Lecture 26 Lesson 09
Lecture 27 Coding Exercises with Solutions
Section 10: Data Visualization with Pandas
Lecture 28 Data Visualization with Pandas
Lecture 29 Lesson 10
Lecture 30 Coding Exercises with Solutions
Aspiring data scientists and analysts looking to enhance their data manipulation skills.,Python developers seeking to expand their knowledge of data-centric libraries.,Professionals interested in learning how to handle and analyze data more efficiently using Python Pandas.

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