Exercises

Here are some exercises to work through in your own time.

Exercise 4

Using stata fetch the sysauto dataset using

sysuse auto

Part 1:

Use the integrated workflows to transfer the weight and price variables to python and save the results in a pd.DataFrame called data.

>>> data
    weight  price
0     2930   4099
1     3350   4749
2     2640   3799
3     3250   4816
4     4080   7827
..     ...    ...
69    2160   7140
70    2040   5397
71    1930   4697
72    1990   6850
73    3170  11995

[74 rows x 2 columns]

Part 2:

Use statsmodels to run a simple OLS regression of weight ~ price and then run this regression in stata.

Exercise 5

Use the yfinance package in python to fetch the last 3 months of Close prince data for:

  1. Amazon (AMZN)

  2. Microsoft (MSFT)

  3. Game Stop (GME)

and construct a dataframe.

Part 1:

Choose to use either the integrated workflows or file based workflow to transfer the last three months of stock price data (“closing price”) to stata

Run a simple ols regression:

  1. comparing AMZN and MSFT stock price histories

  2. comparing AMZN and GME stock price histories

Part 2:

Choose either stata or python to normalize each stock price history by dividing the column by the first price of each stock.

The dataframe should look like

../../_images/python-yfinance-stock-price-normalised.png

and make a plot comparing the three time series.

Integrations with Other Languages Session 8 (SQL, Scraping, and Workflow)