Advanced Data Analysis & Wrangling with Python Pandas

Description

This course of the Fantastic Python Series is an advanced course on data manipulation and wrangling with the pandas package in Python. Pandas is one of the most important packages in the Python eco-system and it is where most data scientists spend 80% of their time on. It is essential to have a deep and complete understanding of how pandas work to conduct analysis more effectively and efficiently.

This course offers a complete guide on all areas of Pandas functionalities, from the foundamentals, all the way to highly advanced and complex skills such as rolling windows and time series resampling. It will teach data scientists from all fields, including IT, business, finance, etc, how data manipulation and wrangling is done effectively in pandas and how to avoid potential pitfalls ("Gotchas").

The advanced parts of this course is particularly helpful for those analysts/scientists who work with time series data (and panel data) as the pandas offers an extensive array of features for time series calculations. So finance professionals and physists will find it especially relevant to their field of work.

This course is proceeds from the foundations of data series and data frame, and then proceeds to intermediate level data manipulations, and eventually dive deep into advanced data wrangling topics such as complex groupby operations, sophisticated joins/merges and reshaping from wide format to long and vice versa.

Finally, a stock market case study is offered as a capstone for this entire course. This case study will draw together most, if not all, areas of knowledge of pandas and analyze real-world financial data.

What You Will Learn!

• Learn Python pandas package for advanced data analysis and wrangling
• Data Frames & Series
• Input and Output into Pandas
• Data selection and filtering
• Sort, count, unique, duplicated values
• Handling missing values
• Data Aggregation
• Data Transformation
• apply, map
• Complex Groupby (Split-Apply-Combine)
• Vectorized string manipulation
• Vectorized date/time manipulation
• reshape and pivot
• Joins/Merge
• Rolling Windows Operations
• Data Visualization
• Stock Market Case Study

Who Should Attend!

• Data Analysts & Data Scientists
• Anyone who is interested in series data manipulation and wrangling in Python
• Researchers in all fields
• Business analysts and marketing researchers

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