Ex.0 Test your setup

Author
Affiliation

Eduard Bukin

Distributional Impact of Policies. Fiscal Policy and Growth Department

This example is in ex00-positron-test, which should be in C:/WBG/ai/ on your computer if you followed the setup instructions correctly. Open this folder as a project in Positron to ensure that all file paths work correctly.

Objective

This exercise verifies that your software environment is correctly set up for the course. Each file in this folder runs a small analysis that exercises a different language or tool. If every file runs without errors, your setup is ready.

What is being tested

File Language / Tool What it checks
test-r.R R tidyverse, ggplot2, palmerpenguins, OLS regression
test-python.py Python pandas, seaborn, matplotlib, statsmodels, scikit-learn
test-jupyter.ipynb Python (Jupyter) Same Python stack inside a Jupyter notebook
test-quarto.qmd Quarto + R Quarto rendering with R code chunks, knitr, broom
test-stata.do Stata Data generation, regression, and graphing

How to run each file

  1. Open the file in Positron (or VS Code).
  2. Run it:
    • R script (test-r.R) — Open the file and click the Run button (or press Ctrl+Shift+Enter to run all lines). The R console will execute the script.
    • Python script (test-python.py) — Open the file and click Run (or press Ctrl+Shift+Enter). The Python console will execute the script.
    • Jupyter notebook (test-jupyter.ipynb) — Open the notebook, then click Run All in the toolbar to execute every cell.
    • Quarto document (test-quarto.qmd) — Open the file and click the Render button (or run quarto render test-quarto.qmd in the terminal) to produce an HTML report.
    • Stata do-file (test-stata.do) — Open the file and click Run (or execute do test-stata.do in Stata).
  3. Check the output. Each file should produce tables, plots, or regression output without errors. If something fails, the error message will tell you which package or dependency is missing.

Expected outcome

  • Four ggplot2 charts and an OLS summary (R)
  • Four seaborn/matplotlib charts and an OLS summary (Python script and notebook)
  • A rendered HTML document with figures, tables, and inline statistics (Quarto)
  • Three Stata graphs, summary statistics, and a regression table (Stata)

If all files run successfully, your environment is ready for the course.