Data Preparation in Python
Before analyzing data, we spend considerable effort wrangling the data into an analyzable form — creating and recoding variables, merging data sets, filtering and aggregating data, reshaping and more. In this workshop, we’ll learn about data preparation using Python3 and pandas, “providing fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive.” We’ll also cover working with data types like factors and dates and using conditional logic. This workshop assumes basic experience using Python3 at the level of our Intro to Python workshop.
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