This repository is a working space for exploring the ANES (American National Election Studies) Time Series Cumulative Data File (CDF) and its accompanying documentation.
raw/anes_timeseries_cdf_csv_20220916.csv– The Cumulative Data File (CSV) released 2022-09-16.raw/anes_timeseries_2024_csv_20250808.csv– A newer (2024) time series data release.raw/anes_timeseries_cdf_codebook_var_20220916.pdf→ converted toraw/anes_timeseries_cdf_codebook_var_20220916.txt.raw/anes_timeseries_cdf_codebook_app_20220916.pdf→ converted toraw/anes_timeseries_cdf_codebook_app_20220916.txt.raw/anes_timeseries_2024_userguidecodebook_20250808.pdf→ converted toraw/anes_timeseries_2024_userguidecodebook_20250808.txt.dev_notebook.ipynb– Scratch / exploratory notebook (includes PDF→text extraction snippet using PyMuPDF).socsci_venv/– Local Python virtual environment (not intended for distribution).
| File | Primary Content Focus | Typical Sections | How to Use It Programmatically |
|---|---|---|---|
anes_timeseries_cdf_codebook_var_20220916.txt |
Variable-level documentation | Variable name, label, question text, universe, coding categories / value labels, notes, sometimes weighting or comparability notes inline | Parse to build a structured data dictionary (variables, types, value labels). Anchor on consistent variable header patterns (e.g., variable name followed by label). |
anes_timeseries_cdf_codebook_app_20220916.txt |
Appendices and methodological reference material | Study design, sampling, weighting schemes, derived scale construction, panel composition, response rates, longitudinal notes, possibly index construction tables | Use as narrative reference; limited structured extraction value except for targeted sections (e.g., weight construction). |
In short: the _var_ file is the operational codebook for programmatic parsing; the _app_ file supplies contextual and methodological appendices that explain how certain variables, weights, or composite indices came to be.
- Reproducibility: Methodological notes (appendix) justify analysis choices (e.g., which weight to apply).
- Data Integrity: Variable-level metadata alone can be ambiguous without appendix definitions (e.g., construction of feeling thermometers or ideology scales).
- Traceability: When publishing results, you can cite specific appendix sections that clarify transformations or sampling adjustments.
- Selecting the correct weight variable(s) (e.g., post-stratification vs. panel weights).
- Understanding changes in question wording across waves.
- Interpreting composite scales or index construction steps.
- Clarifying sampling frames or subsample restrictions that explain missingness patterns.
Two distinct data assets exist in this workspace:
| File | Coverage | Status Relative to CDF | Notes |
|---|---|---|---|
raw/anes_timeseries_cdf_csv_20220916.csv |
1948–2020 (per CDF release vintage 2022-09-16) | Canonical cumulative (integration already performed by ANES) | Variable names / codes standardized up through 2020. |
raw/anes_timeseries_2024_csv_20250808.csv |
2024 wave (and only 2024) | NOT yet merged into cumulative file | Naming / coding may differ; new variables; potential reworded or retired items. |
Goal: Harmonize the 2024 release with the cumulative data so analyses can span 1948–2024 pending an official updated CDF.
raw/anes_timeseries_2024_userguidecodebook_20250808.txt is a text extraction of the 2024 release's combined user guide + codebook PDF. It blends:
- Study-level documentation (design, sampling, weighting, methodological 2024 updates).
- Variable-level descriptions (new or modified items vs. 2020 and earlier waves).
- Analyst guidance (recommended weights, handling break-offs, derived constructs).
Unlike the historical split (variable vs appendix) for the CDF, 2024 co-locates both layers. For harmonization we conceptually partition it into:
- Variable metadata blocks (feed a parser akin to the CDF variable codebook)
- Methodological sections (justify mapping and transformation decisions)