Introduction to Python for Data Analysis
University of Utah
Registration: Use the following link to sign up for this workshop.
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General Information
What: This workshop will introduce the basics of the Python programming language for data science, with a focus on working with tabular data using the Pandas library.
Who: The course is aimed at graduate students, postdocs, faculty, and other researchers across campus who are interested in learning how to use Python for data analysis. You don’t need to have coding experience or any previous knowledge of Python to attend this workshop.
Requirements: Participants must bring a laptop on which they can access the internet via a web browser. We will be using Google Colab notebooks throughout this workshop.
Contact: Please email penny.atkins@hsc.utah.edu or rebecca.barter@hsc.utah.edu for more information.
Schedule
Day 1
| Time | Topic | Incomplete notebook | Complete notebook |
|---|---|---|---|
| 9:00 | Introduction and Setup | ||
| 9:30 | Variables | 01_variables | 01_variables_complete |
| 10:00 | Types | 02_types | 02_types_complete |
| 10:30 | Morning Break | ||
| 11:00 | Type conversions | 03_type_conversions | 03_type_conversions_complete |
| 11:30 | Boolean operations | 04_boolean_operations | 04_boolean_operations_complete |
| 12:00 | Lunch | ||
| 1:00 | The numpy library | 05_numpy | 05_numpy_complete |
| 1:45 | The pandas library | 06_pandas_dataframes | 06_pandas_dataframes_complete |
| 2:30 | Afternoon Break | ||
| 3:00 | Data frame indexes | 07_index | 07_index_complete |
| 3:30 | Pandas series | 08_series | 08_series_complete |
| 4:00 | End |
Day 2
| Time | Topic | Incomplete notebook | Complete notebook |
|---|---|---|---|
| 9:00 | Subsetting with [] and .loc |
09_subsetting | 09_subsetting_complete |
| 9:45 | Filtering rows using logical conditioning | 10_filtering_logical | 10_filtering_logical_complete |
| 10:00 | Filtering rows using .query |
11_filtering_query | 11_filtering_query_complete |
| 10:15 | Positional indexing with .iloc |
12_iloc | 12_iloc_complete |
| 10:30 | Morning Break | ||
| 11:00 | Adding and dropping columns from DataFrames | 13_modifying_dataframes | 13_modifying_dataframes_complete |
| 11:30 | Computing summaries of DataFrames | 14_summarizing_dataframes | 14_summarizing_dataframes_complete |
| 12:00 | Lunch | ||
| 1:00 | Grouped computations | 15_grouped_computations | 15_grouped_computations_complete |
| 1:30 | Data visualization | 16_visualization | 16_visualization_complete |
| 2:30 | Afternoon Break | ||
| 3:00 | Lists and iteration | 17_list_comprehension | 17_list_comprehension_complete |
| 4:00 | End |