85 lines
5.1 KiB
Markdown
85 lines
5.1 KiB
Markdown
# MIL-003: Read and analyse with pandas
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## Metadata
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| Key | Value |
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| --- | --- |
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| ID | MIL-003 |
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| CrossReference | [BC-001] |
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| Language | en |
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| Domain | it |
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## Version History
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| Date | Status | Author | Reviewer | Change | Commit |
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| --- | --- | --- | --- | --- | --- |
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| 2026-10-13 | Accepted | Jens Tirsvad Nielsen | AI as stand-in for S01 | Initial version, reviewed in RC-006 (Go) | [165e91a] |
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---
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## Purpose
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This gate decides whether the pandas half of both lectures is delivered: the data file is read in one line, the `DataFrame` and `Series` are used, converted to a dictionary and a list, and the average and maximum temperature and the row selections are computed. The work is delivered on the branch `mil-003-pandas-analysis` and one pull request.
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## Deliverable
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`src/weather/analysis.py` with `read_data`, `to_data_dict`, `to_temp_list`, `average_temp`, `average_temp_mean`, `max_temp`, `row_for_day`, `hottest_row` and `day_in_fahrenheit`, the `pandas` extra in `pyproject.toml` used as designed, and `tests/test_analysis.py`.
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## Go / No-Go Criteria
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| # | Criterion (objectively checkable) | Go | No-Go |
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| --- | --- | --- | --- |
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| 1 | `read_data` returns a `DataFrame` | `isinstance(data, pandas.DataFrame)`, 7 rows, columns `day`, `temp`, `condition`; the body is one `pandas.read_csv` call | Another type, or a different row or column count |
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| 2 | A column is a `Series` | `isinstance(data["temp"], pandas.Series)` | Another type |
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| 3 | The conversions work | `to_data_dict(data)` has the keys `day`, `temp`, `condition`; `to_temp_list(data)` is `[12, 14, 15, 14, 21, 22, 24]` | A wrong key or value |
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| 4 | The average is right two ways | `average_temp` (sum and length) and `average_temp_mean` (`Series.mean()`) both give 17.428571... | The two ways differ, or a wrong value |
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| 5 | The maximum is right | `max_temp(data)` is 24 | A different value |
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| 6 | Row selection is right | `row_for_day(data, "Monday")` is one row with `condition` `Sunny` and `temp` 12; `hottest_row(data)` is the row of Sunday | A wrong row or an empty result |
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| 7 | Fahrenheit is right | `day_in_fahrenheit(data, "Monday")` is 53.6 | A different value |
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| 8 | The `csv` part still needs no dependency | `dependencies = []` and `import weather.csv_reader` works without `pandas` | A dependency added, or `csv_reader` imports `pandas` |
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| 9 | The `csv` and `pandas` readers agree | `to_temp_list(read_data())` equals `read_temperatures()` | The lists differ |
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| 10 | Tests are green | `pytest` exit code 0 | A failing test |
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| 11 | The code is reviewed | `RC-*` against `QC-PY-001` has the verdict `Go` | Verdict `No-Go` or `Go-with-conditions` |
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## Dependencies
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| Depends on | Reason |
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| --- | --- |
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| [MIL-002] accepted and merged | The data file and the `csv` reader are the reference for the agreement test |
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## Traceability
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| Business Case objective / KPI / user story | Reference |
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| --- | --- |
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| Objective 3: reading with `pandas` | [BC-001], criterion 3 in Success Criteria |
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| Objective 4: conversions | [BC-001], criterion 3 in Success Criteria |
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| Objective 5: average and maximum | [BC-001], criterion 4 in Success Criteria |
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| Objective 6: row selection and Fahrenheit | [BC-001], criterion 5 in Success Criteria |
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| Objective 9: `pandas` is an extra | [BC-001], criterion 10 in Success Criteria |
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## Ownership
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| Role | Stakeholder ID (SA) |
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| --- | --- |
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| Owner | S01 |
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| Approving reviewer | S01 |
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## Target Date
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2026-10-19 — third of five gateways, inside the plan of [PP-001] that ends 2026-10-23.
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## Tasks
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| # | Task | Summary | Needs its own Use Case/User Story? | Reference |
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| --- | --- | --- | --- | --- |
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| 1 | Read the weather data with pandas | Add `read_data(path)` in `src/weather/analysis.py`: one `pandas.read_csv` call returning the `DataFrame` `data`; the default path is the data file. `pandas` is imported only in this module. Serves objective 3. | No | |
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| 2 | Convert the data to a dictionary and a list | Add `to_data_dict(data)` (`DataFrame.to_dict()`) and `to_temp_list(data)` (`data["temp"].to_list()`), as the lecture does. Serves objective 4. | No | |
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| 3 | Compute the average and maximum temperature | Add `average_temp(data)` that returns the sum of `temp_list` divided by its length, and `average_temp_mean(data)` that uses `Series.mean()`, so the two ways of the lecture can be compared; add `max_temp(data)` with `Series.max()`. Serves objective 5. | No | |
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| 4 | Select rows by a condition | Add `row_for_day(data, day)` (`data[data.day == day]`), `hottest_row(data)` (`data[data.temp == data.temp.max()]`) and `day_in_fahrenheit(data, day)` (`temp * 9 / 5 + 32`, factors from `constants.py`). Serves objective 6. | No | |
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| 5 | Add the tests for the pandas analysis | Add `tests/test_analysis.py` for the criteria of this gateway, including that the two readers agree. The test module is skipped with `pytest.importorskip` when `pandas` is missing. | No | |
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---
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[BC-001]: ../business-case.md
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[PP-001]: ../project-plan.md
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[MIL-002]: ./mil-002-read-with-csv.md
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[165e91a]: https://git.tirsystem.com/Tirsvad-Udemy-100-days-of-code/025-weather/commit/165e91a0183c6351fbfdad53b050bb2918275e6d
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