Advanced Pandas (2021)
1h 2mAdvanced2021-02-01
Authors

Brett Vanderblock
Data Scientist with Patagonia and Cofounder of Think Fast Analytics

Madecraft
Full-Service Learning Content Company
Course details
If you've worked in Python, you're likely familiar with the basic of pandas. In this advanced course, instructor Brett Vanderblock shares how you can take advantage of the advanced functions of pandas—such as working with dates, dealing with missing data, merging DataFrames, and more—to work more effectively with your data. First, Brett introduces you to DataFrames, identifies the top functions in pandas, and shows you how to configure your pandas workspace efficiently. He walks you through converting data types, working with strings, and using the apply map and applymap functions effectively. He shows you how to combine Groupby and multiple aggregate functions in pandas and how to use the merge, join, and concat functions. Brett steps through plotting and statistical functions with pandas. He concludes by explaining how you can use pandas-profiling and Geopandas to get the most out of your functions and data.
Skills covered
pandasPythonData AnalysisData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen SourceDeep Dive (X:Y)
Concepts
0. Introduction
- 01 - Take pandas to the next level
1. From Beginner to Advanced pandas
- 02 - Getting started with pandas
- 03 - Intro to DataFrames using pandas
- 04 - Top functions using pandas
- 05 - Configuring options using pandas
2. Advanced Calculations
- 06 - Data type conversions using pandas
- 07 - Working with strings using pandas
- 08 - Working with dates using pandas
- 09 - Dealing with missing data using pandas
- 10 - Apply Map Applymap
3. Transforming Dataframes
- 11 - Groupby and aggregations using pandas
- 12 - Reshaping dataframes (pivot, stack)
- 13 - Merging (merge, join) and concatenating (concat) dataframes
- 14 - Mapping variables into groups
4. Exploratory Data Analysis & Visualization
- 15 - Plotting with pandas
- 16 - Correlations and statistical functions
5. Beyond pandas
- 17 - Accelerate EDA with pandas-Profiling
- 18 - Explore Geographic data with Geopandas
- 19 - Beyond pandas with Dask and Koalas (Spark)
Conclusion
- 20 - Your path forward using advanced pandas functions
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