Course Information
Course Overview
Learn Advanced Data Wrangling, Analytics & Manipulation with pandas
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.
Course Content
- 10 section(s)
- 121 lecture(s)
- Section 1 Introduction
- Section 2 Installation of Python, Pandas and Jupyter Notebook
- Section 3 Series in Pandas
- Section 4 DataFrame: An Introduction
- Section 5 Read and Write Data Files
- Section 6 Data Selection and Filtering
- Section 7 Sorting, Counting, Uniquing and Dealing with Duplicated Values
- Section 8 Missing Values Handling
- Section 9 Aggregation
- Section 10 Transformation
What You’ll 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
Skills covered in this course
Reviews
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EEzeadiefe Fidelis Adimabua
Nice course
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EEl Amma
thank you
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DDaniel Boasberg
Looks that way, yes!
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FFabio Schapowal
I really enjoyed the course. The explanations were direct and simple, with practical examples of common mistakes. I was able to learn without having to rewatch the videos. To improve, it lacked exercises for reinforcement.