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Merge pull request #94 from igerber/fix/tutorial-notebook-and-skill
Fix tutorial notebook syntax error and clean up metadata
2 parents ff10253 + d8fb598 commit 4e7942d

11 files changed

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‎.claude/commands/validate-tutorial.md‎

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@@ -55,12 +55,12 @@ The user may provide an optional argument: `$ARGUMENTS`
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- Success: "01_basic_did.ipynb - PASSED"
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- Failure: Show the error message and which cell failed
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4. **Clear outputs** after validation completes (regardless of pass/fail):
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4. **Clear outputs and metadata** after validation completes (regardless of pass/fail):
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```bash
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jupyter nbconvert --ClearOutputPreprocessor.enabled=True --inplace "docs/tutorials/NOTEBOOK.ipynb"
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jupyter nbconvert --ClearOutputPreprocessor.enabled=True --ClearMetadataPreprocessor.enabled=True --inplace "docs/tutorials/NOTEBOOK.ipynb"
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```
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This ensures notebook outputs are not committed to git.
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This ensures notebook outputs and execution metadata (timestamps, execution counts) are not committed to git.
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5. **Summary**: After all notebooks complete, show a summary like:
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```
@@ -72,7 +72,7 @@ The user may provide an optional argument: `$ARGUMENTS`
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## Notes
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- Notebooks are executed to validate they work, then outputs are cleared
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- Notebooks are executed to validate they work, then outputs and metadata are cleared
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- If a notebook fails, continue to the next one (don't stop early)
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- The working directory should be the project root
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- Some notebooks may take a while to run (especially those with bootstrap)

‎docs/tutorials/01_basic_did.ipynb‎

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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:35.801900Z",
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"iopub.status.busy": "2026-01-18T18:10:35.801757Z",
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"iopub.status.idle": "2026-01-18T18:10:36.233206Z",
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"shell.execute_reply": "2026-01-18T18:10:36.232925Z"
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}
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.234607Z",
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"iopub.status.busy": "2026-01-18T18:10:36.234517Z",
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"iopub.status.idle": "2026-01-18T18:10:36.239917Z",
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"shell.execute_reply": "2026-01-18T18:10:36.239725Z"
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}
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"# Generate synthetic DiD data with known ATT of 5.0\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.251493Z",
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"iopub.status.busy": "2026-01-18T18:10:36.251420Z",
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"iopub.status.idle": "2026-01-18T18:10:36.254312Z",
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"shell.execute_reply": "2026-01-18T18:10:36.254088Z"
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}
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"# Examine the data structure\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.255333Z",
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"iopub.status.busy": "2026-01-18T18:10:36.255268Z",
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"iopub.status.idle": "2026-01-18T18:10:36.257620Z",
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"shell.execute_reply": "2026-01-18T18:10:36.257437Z"
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}
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"# Create the estimator\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.258588Z",
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"iopub.status.busy": "2026-01-18T18:10:36.258510Z",
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"iopub.status.idle": "2026-01-18T18:10:36.260137Z",
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"shell.execute_reply": "2026-01-18T18:10:36.259955Z"
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}
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"# Access individual components\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.261002Z",
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"iopub.status.busy": "2026-01-18T18:10:36.260952Z",
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"iopub.status.idle": "2026-01-18T18:10:36.262794Z",
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"shell.execute_reply": "2026-01-18T18:10:36.262624Z"
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}
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"# Using formula interface (R-style)\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.263682Z",
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"iopub.status.busy": "2026-01-18T18:10:36.263631Z",
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"iopub.status.idle": "2026-01-18T18:10:36.265008Z",
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"shell.execute_reply": "2026-01-18T18:10:36.264810Z"
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}
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},
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"metadata": {},
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"# Verify both methods give the same result\n",
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{
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.265866Z",
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"iopub.status.busy": "2026-01-18T18:10:36.265814Z",
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"iopub.status.idle": "2026-01-18T18:10:36.268138Z",
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"shell.execute_reply": "2026-01-18T18:10:36.267940Z"
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}
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},
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"metadata": {},
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"source": [
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"# Add some covariates to our data\n",
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"execution_count": null,
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.269011Z",
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"iopub.status.busy": "2026-01-18T18:10:36.268965Z",
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"iopub.status.idle": "2026-01-18T18:10:36.270317Z",
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"shell.execute_reply": "2026-01-18T18:10:36.270123Z"
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}
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},
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"metadata": {},
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"outputs": [],
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"# All coefficient estimates are available\n",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.271191Z",
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"iopub.status.busy": "2026-01-18T18:10:36.271130Z",
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"iopub.status.idle": "2026-01-18T18:10:36.274752Z",
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"shell.execute_reply": "2026-01-18T18:10:36.274501Z"
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}
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},
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"metadata": {},
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"# Generate data with more structure\n",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.275657Z",
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"iopub.status.busy": "2026-01-18T18:10:36.275605Z",
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"iopub.status.idle": "2026-01-18T18:10:36.277635Z",
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"shell.execute_reply": "2026-01-18T18:10:36.277443Z"
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}
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"metadata": {},
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"# Using fixed effects with dummy variables\n",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.278482Z",
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"iopub.status.busy": "2026-01-18T18:10:36.278432Z",
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"iopub.status.idle": "2026-01-18T18:10:36.280535Z",
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"shell.execute_reply": "2026-01-18T18:10:36.280352Z"
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"metadata": {},
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"# Using absorbed fixed effects (within-transformation)\n",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.281443Z",
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"iopub.status.busy": "2026-01-18T18:10:36.281372Z",
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"iopub.status.idle": "2026-01-18T18:10:36.284078Z",
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"shell.execute_reply": "2026-01-18T18:10:36.283923Z"
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}
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"metadata": {},
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"source": [
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"# Two-Way Fixed Effects estimator\n",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.285055Z",
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"iopub.status.busy": "2026-01-18T18:10:36.284989Z",
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"metadata": {},
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"# Create clustered data\n",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.288239Z",
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"iopub.status.busy": "2026-01-18T18:10:36.288176Z",
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"iopub.status.idle": "2026-01-18T18:10:36.290659Z",
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"metadata": {},
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"# Compare standard errors: robust vs cluster-robust\n",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-01-18T18:10:36.291566Z",
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"iopub.status.busy": "2026-01-18T18:10:36.291505Z",
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"metadata": {},
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"# Wild cluster bootstrap inference\n",
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"metadata": {},
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"# Compare inference methods\n",
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"metadata": {},
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"# Export to dictionary\n",
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"# Export to DataFrame (useful for combining multiple estimates)\n",
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"language_info": {
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"name": "ipython",
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"version": 3
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"file_extension": ".py",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.4"
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"name": "python"
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"nbformat": 4,

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