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Python Camp I
Python Basics
Getting started with Anaconda (7:22)
Jupyter notebooks (13:07)
Python Basics I (13:48)
Python Basics II (11:14)
Python Basics III (21:59)
Student Exercise: Python Basics (18:08)
Numpy & Pandas
Jupyter Notebook: Numpy
Intro to Numpy (7:47)
Numpy II (5:19)
Numpy III (9:37)
Numpy IV (9:07)
Student Exercise: Numpy (15:50)
Jupyter notebook: Pandas
Introduction to Pandas (10:38)
Tidy Data (6:37)
DataFrames, Part 1 (15:09)
DataFrames, Part II (18:36)
Student Exercise: Pandas (17:25)
Applied Python
Reading and filtering data (24:41)
Missing data (19:22)
Grouping and Summary Stats (26:36)
Stacking and Merging (15:18)
Folders and Functions (45:58)
Capstone: Python for Research
Bring in and inspect data (17:42)
Exercise 1 (11:40)
Create variables / lagged variables / indicator variables (26:14)
Exercise 2 (17:23)
Missing values and outliers (19:35)
Exercise 3 (21:34)
Merging data one-to-one (27:39)
Exercise 4 (11:46)
Complex merging / Adjusting dates / groupby (24:36)
Exercise 5 (24:59)
Computing stock returns (15:48)
Exercise 6 (14:33)
Ranking and summary statistics (14:26)
Regression in Python (13:59)
Exercise 7 (18:57)
Optional: Accessing WRDS with Python
Intro to WRDS with Python (31:29)
Accessing Compustat Annual with Python (16:43)
Accessing Compustat Quarterly with Python (7:40)
Saving data permanently (9:08)
Accessing CRSP with Python (16:05)
Teach online with
Complex merging / Adjusting dates / groupby
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