This course, "Pandas & Numpy for Data Science - The Right Way 2024," is designed to give you a deep understanding of the Pandas and Numpy libraries, which are essential for data science in Python. You'll start with Numpy, learning how to create and manipulate different types of arrays, from simple 1-D and 2-D arrays to more complex 3-D and 4-D arrays. You'll explore array operations, slicing, indexing techniques, and advanced functions for arithmetic, logical, and statistical operations. Topics like reshaping arrays, broadcasting, and understanding the differences between views and copies will also be covered.
"Pandas is an indispensable tool for data analysis in Python. Its powerful data structures and functions simplify data manipulation and analysis."
— Wes McKinney, author of "Python for Data Analysis" and the creator of Pandas.
In the Pandas section, you'll dive into working with Series and DataFrames, which are powerful data structures for handling and analyzing data. You'll learn how to create, manipulate, and inspect DataFrames, handle missing data, perform conditional selections, and reindex. The course also covers data input and output, including reading from and writing to various file formats like CSV, Excel, HTML, and SAS. You'll gain skills in data processing, such as renaming columns, applying functions, and sorting data.
Advanced topics include grouping and aggregation, creating pivot tables, and merging and joining DataFrames. You'll learn techniques for concatenating DataFrames, handling duplicates, and manipulating string data within DataFrames. By the end of this course, "Pandas & Numpy for Data Science - The Right Way 2024", you'll have a solid foundation in using Pandas and Numpy for data analysis, enabling you to tackle real-world data science problems with confidence and efficiency.
"NumPy is the backbone of the scientific Python ecosystem, providing the essential building blocks for data analysis, machine learning, and more."
— Wes McKinney, creator of Pandas.
Pandas & Numpy for Data Science - The Right Way 2024 Table of Contents:
- Anaconda and Jupyter Notebook (3 lectures - 25 min)
- Anaconda Installation (09:26)
- Introduction to Anaconda and Jupyter NB (07:01)
- Jupyter Notebook Interface (08:05)
- Advanced Data Structure using Numpy (9 lectures - 2 hr 35 min)
- Numpy Introduction (15:49)
- Numpy Array Creation (15:51)
- Numpy arange and Reshape (10:45)
- Numpy Array Conversion (13:28)
- Accessing Array Values (22:44)
- Numpy Operations (23:00)
- Fancy Indexing and Sorting Arrays (15:38)
- Array Products and Concatenation (23:11)
- Broadcasting (14:50)
- Introduction to Pandas Module for Data Manipulation (14 lectures - 3 hr 49 min)
- Introduction (04:34)
- Pandas Series (21:23)
- Pandas DataFrames (24:43)
- Handling Missing Data (25:56)
- Conditional Selection and Reindexing of a DataFrame (11:56)
- Data Input and Data Output (19:38)
- Data Processing (22:37)
- Grouping and Pivot Tables (15:59)
- Concatenating DataFrames and Inserting New Rows (13:05)
- Merging and Joining DataFrames (15:04)
- Cartesian Product between DataFrames (05:15)
- Handling Duplicates in a DataFrame (12:31)
- Handling Strings (23:03)
- Handling Dates using Pandas Functions (4 lectures - 1 hr 3 min)
- DateTime - Datetime Creation (11:45)
- DateTime - Pandas Datetime Functions (11:40)
- DateTime - Reading Dates with Infarmats (25:44)
- DateTime Series - DateRange and DateOffsets (14:20)
Who is this course for?
- Data Analysts: Learn to manipulate and analyze datasets using Pandas efficiently.
- Data Science and Machine Learning Students: Learn essential skills for handling data in projects and research.
