Advanced Data Analysis & Wrangling with Python Pandas

Learn Advanced Data Wrangling, Analytics & Manipulation with pandas

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


Requirements
Some basic Python coding skill required.
I will teach you everything about 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.
Who this course is for:
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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