Python in Data Science is huge right now. This course covers the basics to get started looking at and manipulating data in Python. We will use the popular Jupyter and Pandas tools to ingest, tweak, visualize, and pivot data. There are ample labs for you to try out the tools on your own.
Topics covered include using notebooks, data structures in pandas, loading data, summary statistics, visualization, pivoting and more. Taking this course will teach you how to leverage the pandas library. You will be much more efficient and productive following this course.
* This course can run two or three days (extra day for visualization with Matplotlib and Seaborn).
Key Learning Areas
- Data Frame
- Ingesting Data
- Serializing Data
- Inspecting Data
- Tweaking Data
- Summary Statistics
- Dealing w/ Missing Data
- Grouping & Pivoting
- Joining Data
This course will cover the skills to be comfortable with pandas and Python. With hands-on labs, you will be able to quickly evaluate your mastery of the topics. The topics are presented with real world data. Finally, there are many labs to make sure that you get the chance to try them out.
Python is wonderful basis to leverage for data analysis. We will explore the pandas library so you can can analyze data. You will quantity data sets using summary statistics and visualize them leveraging the Matplotlib library. If you intend to get into Machine Learning, this is an excellent prerequisite, as much of ML is tweaking the data using a tool like pandas.
This course is for experienced Python developers or analysts who have some experience with Python. Typical attendees are looking to migrate their current analysis from Excel, or other proprietary products to leverage the power and ease of Python.
If you want to leverage Python for analysis or Machine Learning, this course will get you started. If you are on a team using Python and pandas, this will be a great opportunity to get your team on the same page and speaking the same language.
This course assumes the students have solid working knowledge of the Python language.