Data Analysis Crash Course For Beginners (Pandas + Python)
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Fundamentals of Data Analysis. -
Working with Pandas, iPython, Jupyter Notebook. -
Important Jupyter Notebook Commands. -
Working with CSV, Excel, TXT, JSON Files and API Responses. -
Working with DataFrames (Indexing, Slicing, Adding and Deleting).
- Basics of Python
Welcome to Data Analysis Basics with Pandas and Python – For Beginners,
This course will help you to understand the fundamentals of Data Analysis with Python and Pandas library. You will learn,
1. Fundamentals of Data Analysis.
2. Working with Pandas, iPython, Jupyter Notebook.
3. Important Jupyter Notebook Commands.
4. Working with CSV, Excel, TXT, JSON Files and API Responses.
5. Working with DataFrames (Indexing, Slicing, Adding and Deleting).
Pandas is an open-source library providing high-performance, easy-to-use data structures and data analysis tools for Python. Pandas provide a powerful and comprehensive toolset for working with data, including tools for reading and writing diverse files, data cleaning and wrangling, analysis and modelling, and visualization. Fields with the widespread use of Pandas include data science, finance, neuroscience, economics, advertising, web analytics, statistics, social science, and many areas of engineering.
After completing this course you will have a good understanding of Pandas and will be ready to explore Data Analysis in-depth in future.
- Python Programmers and Developers
- Student interested in learning Pandas
