/Intro2Python

Introduction to Data Analysis in Python Workshop

Primary LanguageJupyter NotebookMIT LicenseMIT

Intro 2 Python

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Schedule

Day 1

Approximate Times Topic
9:00 -9:30 Class Orientation
9:30 - 10:15 Data Science Notebooks Orientation
10:15 - 10:30 Break
10:30 - 11:45 Intro to Python's Type System and Key Programming Vocabulary
11:45 - 12:00 Retrospective
12:00 - 13:30 Lunch
13:30 - 14:30 Applying String Methods to Text Analysis
14:30 - 15:45 Intro to Python's Built-In Data Collection Types and Numpy Arrays
15:45 - 16:00 Break
16:00 - 16:50 Basic Plotting with Matplotlib in Data Science Notebooks
16:50 - 17:00 Retrospective

Day 2

Approximate Times Topic
9:00 - 10:00 Numpy Arrays
10:00 - 10:15 Break
10:15 - 11:00 Logical Indexing in Numpy
11:00 - 12:00 Plotting Distributions in Matplotlib
12:00 - 13:30 Lunch
13:30 - 15:30 Matrices in Numpy
15:30 - 15:45 Break
15:45 - 16:50 Basic Image Transformations with Numpy and Matplotlib
16:50 - 17:00 Retrospective

Day 3

Approximate Times Topic
9:00 - 9:30 Warm-Up and Orient to VSCode in GitLab : Lists vs Arrays
9:30 - 10:15 T-tests on Arrays with Scipy-Stats
10:15 - 10:30 Break
10:30 - 11:15 Introduction to Python Dictionaries
11:15 - 11:50 Intro to Pandas DataFrames, Reading and Writing
11:50 - 12:00 Recollect and Reflect
12:00 - 13:30 Lunch
13:30 - 14:45 T-tests on DataFrames with Scipy-Stats and Pingouin
14:45 - 15:00 Break
15:00 - 16:50 DataFrame Selection and Aggregation
16:50 - 17:00 Recollect and Reflect

Day 4

Approximate Times Topic
09:00 - 10:00 Plotting with Pandas
10:00 - 10:15 Break
10:15 - 11:50 DataFrame Selection and Aggregation
11:50 - 12:00 Recollect and Reflect
12:00 - 13:30 Lunch
13:30 - 14:45 DataFrame GroupBy and Seaborn CatPlot
14:45 - 15:00 Break
15:00 - 16:50 Reshaping DataFrames
16:50 - 17:00 Recollect and Reflect

Day 5

Approximate Times Topic
09:00 - 09:30 Project Share
09:30 - 10:20 Filepaths
10:20 - 10:35 Break
10:35 - 11:50 Installing Python Locally
11:50 - 12:00 Recollect and Reflect
12:00 - 13:30 Lunch
13:30 - 14:15 Conditional Flow: If-Else Blocks in Python
14:15 - 15:30 Repeating Work: For Loops in Python
15:30 - 15:45 Break
15:45 - 16:00 Workshop Wrap-Up