Master Pandas and Python for Data Handling [2025]
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This two-in-one video course will teach you to master Python 3, Pandas 2-3, and Data Handling.
Python 3 is one of the most popular programming languages in the world, and Pandas 2 and future 3 is the most powerful, efficient, and useful Data Handling library in existence.
You will learn to master Python’s native building blocks and powerful object-oriented programming. You will design your own advanced constructions of Python’s building blocks and execute detailed Data Handling tasks with Python.
You will learn to master the Pandas library and to use its powerful Data Handling techniques for advanced Data Science, Statistics, and Machine Learning Data Handling tasks. The Pandas library is a fast, powerful, flexible, and easy-to-use open-source data analysis and data manipulation tool, which is directly usable with the Python programming language.
You will learn to:
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Master Python programming with Python’s data structures, data transformers, functions, object orientation, and logic
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Use and design advanced Python constructions and execute detailed Data Handling tasks with Python incl. File Handling
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Use Python’s advanced object-oriented programming and make your own custom objects, functions and how to generalize functions
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Manipulate data and use advanced multi-dimensional uneven data structures
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Master the Pandas library for Advanced Data Handling
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Use the language and fundamental concepts of the Pandas library and to handle all aspects of creating, changing, modifying, and selecting Data from a Pandas DataFrame object
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Use file handling with Pandas and how to combine Pandas DataFrames with Pandas concat, join, and merge functions/methods
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Perform advanced data preparation including advanced model-based imputation of missing data and the scaling and standardizing of data
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Make advanced data descriptions and statistics with Pandas. Rank, sort, cross-tabulate, pivot, melt, transpose, and group data
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[Bonus] Make advanced Data Visualizations with Pandas, Matplotlib, and Seaborn
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Perform Advanced Data Handling
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[Cloud computing]: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources.
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Option: To use the Anaconda Distribution (for Windows, Mac, Linux)
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Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages – golden nuggets to improve your quality of work life.
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And much more…
This course is an excellent way to learn to master Python, Pandas and Data Handling! Data Handling is the process of making data useful and usable for data analysis. Most Data Scientists and Machine Learning Engineers spends about 80% of their working efforts and time on Data Handling tasks.
Being good at Python, Pandas, and Data Handling are extremely useful and time-saving skills that functions as a force multiplier for productivity.
This course is designed for anyone who wants to:
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learn to Master Python 3 from scratch or the beginner level
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learn to Master Python 3 and knows another programming language
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reach the Master – intermediate Python programmer level as required by many advanced Udemy courses in Python, Data Science, or Machine Learning
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learn Data Handling with Python
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learn to Master the Pandas library
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learn Data Handling skills that work as a force multiplier and that they will have use of in their entire career
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learn advanced Data Handling and improve their capabilities and productivity
Requirements:
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Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommended
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Access to a computer with an internet connection
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Programming experience is not needed and you will be taught everything you need
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The course only uses costless software
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Walk-you-through installation and setup videos for Cloud computing and Windows 10/11 is included
This course is the course we ourselves would want to be able to enroll in if we could time-travel and become new students. In our opinion, this course is the best course to learn to Master Python, Pandas, and Data Handling.
Enroll now to receive 25+ hours of video tutorials with manually edited English captions, and a certificate of completion after completing the course!
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1Introduction to Master Pandas and Python for Data HandlingVídeo Aula
Introduction to Master Pandas and Python for Data Handling
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2Setup of the Anaconda Cloud NotebookVídeo Aula
This video describes the setup procedures for using the Anaconda Cloud Notebook
Using Anaconda Cloud Notebook requires internet access and an email address
Note: Anaconda often updates its resources and this may cause minor differences in graphics and procedures
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3Download and installation of the Anaconda Distribution (optional)Vídeo Aula
This video describes the procedures to download and install the Anaconda Distribution for use with this course
Download requires internet access
Video is optional
Note: Anaconda often updates its resources and this may cause minor differences in graphics and procedures
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4The Conda Package Management System (optional)Vídeo Aula
This video describes the Conda Package Management System
Conda requires internet access
Video is optional
Note: Conda is a speedily developing environment and this may cause minor differences in graphics and procedures
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5Overview of Python for Data HandlingVídeo Aula
This video provides an overview of "Python for data handling", teaches you some Python and Data Handling theory, and presents a table of contents for Python for Data Handling as well as some basic information about the Jupyter IDE with dynamic typing, Python programs organization, and some fundamental Python language syntax
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6Python IntegersVídeo Aula
Learn to use Python Integers
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7Python FloatsVídeo Aula
Learn to use Python Floats
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8Python StringsVídeo Aula
Learn to use Python Strings
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9Python String MethodsVídeo Aula
Learn to use some Python string methods to test, search, transform, change, and manipulate string data
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10Python Strings and DateTime ObjectsVídeo Aula
Learn to use date and time data with Python's Datetime module. Learn to calculate time durations and time event data. Learn advanced knowledge about date and time data plus how computers and Python handle datetime data
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11Overview of Python Native Data Storage StructuresVídeo Aula
This video provides an overview of the part of this section about Python's data storage abstractions, the set, tuple, dictionary, and the list
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12Python SetVídeo Aula
Learn to use Python's Set
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13Python TupleVídeo Aula
Learn to use Python's native Tuple and how to unpack Tuples
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14Python DictionaryVídeo Aula
Learn to use Python's native Dictionary
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15Python ListVídeo Aula
Learn to use Python's native List
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16Overview of Python Data Transformers and FunctionsVídeo Aula
An overview of the contents of this subpart of the section, Python's data transformers, and functions
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17Python While-loopVídeo Aula
Learn to use Python's native while-loop with some practical examples
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18Python For-loopVídeo Aula
Learn to use Python's native for-loop with some practical examples
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19Python List Comprehensions for Data Handling [Extra Video]Vídeo Aula
Learn some theory on Python's List Comprehensions. Learn to use Python's List Comprehensions from 1D to 3D with comparisons to ordinary Python Lists and For-Loops.
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20Python Logic Operators and conditional code branchingVídeo Aula
Learn to use some of Python's logic operators and conditional code branching. Use your learned knowledge to edit and tailor basic descriptive statistics at a detailed level
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21Python Functions I: Some theoryVídeo Aula
This video lecture describes the theoretical advantages of Python's functions
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22Python Functions II: create your own functionsVídeo Aula
Learn practical coding with Python's functions. You are introduced to functions and basic protections for functions. You will learn how to create functions from code-examples from earlier video lectures, and you will learn how to generalize functions up to advanced uneven-multitype-object 2-dimensional list of lists.
Learn to create your own functions!
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23Python Object Oriented Programming I: Some theoryVídeo Aula
Learn Python OOP theory relevant for data handling tasks and how object-oriented data structures may affect data handling
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24Python Object Oriented Programming II: create your own custom objectsVídeo Aula
Learn to code object-oriented programming with Python, and to handle Python object-oriented code and custom objects within the ambit of data handling
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25Python Object Oriented Programming III: Files and TablesVídeo Aula
Learn to save files in Python and the practical process of converting custom Python objects to tabular form and saving these into .csv, and Excel files and to load files to Pandas Data Frames
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26Python Object Oriented Programming IV: Recap and MoreVídeo Aula
This video lecture is a recap and extension of earlier video lectures. You will assemble knowledge from earlier lectures into more powerful knowledge. You will learn to construct a tabular data form with additional calculated variables and how to use the tabular data form for plotting, etc. You will learn how Data Handling fits with advanced object-oriented program structures.
