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# Weather Data (Day 25) # Weather Data (Day 25)
Reading CSV weather data in Python, first with the built-in `csv` library and then Reading CSV weather data in Python, first with the built-in `csv` library and then
with `pandas`. It is the day-25 assignment of Udemy's *100 Days of Code: The with `pandas`. It is the day-25 assignment of Udemy's *100 Days of Code: The
Complete Python Pro Bootcamp*. The lectures read the weather of one week from Complete Python Pro Bootcamp*. The lectures read the weather of one week from
`weather_data.csv`, collect the temperatures as whole numbers, and then show how `weather_data.csv`, collect the temperatures as whole numbers, and then show how
`pandas` does the same in one line: a table is a `DataFrame` and a column of it is `pandas` does the same in one line: a table is a `DataFrame` and a column of it is
a `Series`. They convert both to a dictionary and a list, compute the average and a `Series`. They convert both to a dictionary and a list, compute the average and
the maximum temperature, select rows by a condition (the row of Monday, the row of the maximum temperature, select rows by a condition (the row of Monday, the row of
the hottest day, Monday's temperature in Fahrenheit), create a `DataFrame` from a the hottest day, Monday's temperature in Fahrenheit), create a `DataFrame` from a
dictionary, and export it to a CSV file. dictionary, and export it to a CSV file.
The `csv` part has no runtime dependencies; `pandas` is an optional extra. The code The `csv` part has no runtime dependencies; `pandas` is an optional extra. The code
keeps the names of the lectures (`data`, `temperatures`, `temp_list`, `data_dict`, keeps the names of the lectures (`data`, `temperatures`, `temp_list`, `data_dict`,
`average_temp`, `monday`, `to_dict`, `to_list`, `mean`, `max`, `to_csv`) so that you `average_temp`, `monday`, `to_dict`, `to_list`, `mean`, `max`, `to_csv`) so that you
can compare it with your own solution. can compare it with your own solution.
> **Status:** in progress. The project foundation (configuration, constants, ![The program running in a terminal: the rows and temperatures read with the csv library, then the data frame, the dictionary, the list, the average 17.428571428571427, the maximum 24, the row of Monday, the hottest row Sunday, Monday in Fahrenheit 53.6 and the scores frame](docs/images/weather-run.png)
> documentation settings and continuous integration) is in place; the readers and
> the analysis follow in the next milestones, see `docs/project-plan.md`. *`python -m weather` in a terminal: the csv part first, then the pandas part.*
## Requirements > **Status:** finished. The `csv` reader, the `pandas` analysis, the creation and
> export of a `DataFrame` and the program that prints the results are done. A short
- Python 3.13 or newer. > description in English, Danish and Bahasa Melayu is on the wiki of the repository
- `git`, to clone the repository. > (the pages are in `wiki/`).
- Optional: [Doxygen](https://www.doxygen.nl/) to build the source documentation.
- No runtime dependencies. `pandas` (the optional extra `pandas`) is needed for the ## Requirements
second half of the lectures and is installed by the `dev` extra, together with
the development tools (`pytest`, `ruff`, `mypy`). - Python 3.13 or newer.
- `git`, to clone the repository.
## Set up - Optional: [Doxygen](https://www.doxygen.nl/) to build the source documentation.
- No runtime dependencies. `pandas` (the optional extra `pandas`) is needed for the
Clone the repository, then create a local virtual environment `.venv` in its second half of the lectures and is installed by the `dev` extra, together with
root, upgrade `pip` and install the project with its development tools. The the development tools (`pytest`, `ruff`, `mypy`).
`.venv` folder is ignored by git.
## Set up
```bash
git clone https://git.tirsystem.com/Tirsvad-Udemy-100-days-of-code/025-weather.git Clone the repository, then create a local virtual environment `.venv` in its
cd 025-weather root, upgrade `pip` and install the project with its development tools. The
``` `.venv` folder is ignored by git.
### Windows powershell ```bash
git clone https://git.tirsystem.com/Tirsvad-Udemy-100-days-of-code/025-weather.git
```powershell cd 025-weather
python -m venv .venv ```
.\.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip ### Windows powershell
python -m pip install -e ".[dev]"
``` ```powershell
python -m venv .venv
If PowerShell refuses to run the activation script, allow scripts for this .\.venv\Scripts\Activate.ps1
window only with `Set-ExecutionPolicy -Scope Process -ExecutionPolicy RemoteSigned` python -m pip install --upgrade pip
and activate again. python -m pip install -e ".[dev]"
```
### Linux debian
If PowerShell refuses to run the activation script, allow scripts for this
Debian 13 or newer ships Python 3.13. On older releases install Python 3.13 window only with `Set-ExecutionPolicy -Scope Process -ExecutionPolicy RemoteSigned`
separately. and activate again.
```bash ### Linux debian
sudo apt install python3 python3-venv
python3 -m venv .venv Debian 13 or newer ships Python 3.13. On older releases install Python 3.13
source .venv/bin/activate separately.
python -m pip install --upgrade pip
python -m pip install -e ".[dev]" ```bash
``` sudo apt install python3 python3-venv
python3 -m venv .venv
### MacOS source .venv/bin/activate
python -m pip install --upgrade pip
```bash python -m pip install -e ".[dev]"
brew install python@3.13 ```
python3.13 -m venv .venv
source .venv/bin/activate ### MacOS
python -m pip install --upgrade pip
python -m pip install -e ".[dev]" ```bash
``` brew install python@3.13
python3.13 -m venv .venv
To install only what the `csv` part needs, leave out the extras: source .venv/bin/activate
`python -m pip install -e .`. To add `pandas` without the development tools use python -m pip install --upgrade pip
`python -m pip install -e ".[pandas]"`. python -m pip install -e ".[dev]"
```
## Run
To install only what the `csv` part needs, leave out the extras:
With the virtual environment active, the program that prints the results of the `python -m pip install -e .`. To add `pandas` without the development tools use
lectures is added in a later milestone (`python -m weather`); until then the `python -m pip install -e ".[pandas]"`.
package can be imported:
## Run
```bash
python -c "from weather import constants; print(constants.DATA_FILE)" With the virtual environment active, print the results of the lectures:
```
```bash
## Run the tests python -m weather
```
The tests write only into temporary folders.
The program prints, in the order of the lectures:
```bash
pytest 1. the rows of `weather_data.csv` and the temperatures as whole numbers, read with
``` the `csv` library (no `pandas` needed);
2. the same file read with `pandas` as a `DataFrame`, converted to a dictionary and
The same checks that continuous integration runs: a list;
3. the average temperature, computed by hand and with `mean`, and the maximum;
```bash 4. the row of Monday, the row of the hottest day, and Monday in Fahrenheit;
python -m pytest 5. a `DataFrame` created from a dictionary of students and scores.
python -m ruff check src tests
python -m ruff format --check src tests Nothing is written to disk unless you ask for it. To also export the scores table
python -m mypy to a CSV file, give a path:
```
```bash
## Continuous integration python -m weather --export new_data.csv
```
`.gitea/workflows/ci.yml` runs on Gitea Actions on every push and on every pull
request. It sets up Python 3.13, upgrades `pip`, installs `.[dev]`, then runs If `pandas` is not installed the `csv` part is still printed, a message names the
`pytest`, `ruff` (lint and format check) and `mypy`. It does not build the source extra to install, and the exit code is 1.
documentation: run `doxygen Doxyfile` yourself, as the next section shows.
The functions can also be used from your own code:
The workflow lives in `.gitea/workflows` and not in `.github/workflows`, so
GitHub does not run it and pushing to a GitHub mirror needs no workflow ```python
permission. from weather.csv_reader import read_temperatures
from weather.analysis import read_data, average_temp, max_temp
## Build the source documentation
temperatures = read_temperatures() # [12, 14, 15, 14, 21, 22, 24]
The source is documented with Doxygen comments and the `Doxyfile` in the root. data = read_data() # a pandas DataFrame
Install Doxygen (`winget install DimitriVanHeesch.Doxygen` on Windows, print(average_temp(data), max_temp(data))
`sudo apt install doxygen` on Debian, `brew install doxygen` on macOS), then: ```
```bash The default data file is the `weather_data.csv` inside the package, so the
doxygen Doxyfile functions work from any folder; pass a `path` to read another file.
```
## Run the tests
The HTML is written to `build/doxygen/index.html`. A warning fails the build.
The tests write only into temporary folders.
## Project layout
```bash
```text pytest
. ```
├── .gitea/workflows/ci.yml continuous integration (Gitea Actions)
├── docs/ business case, plan, milestones, reviews The same checks that continuous integration runs:
├── src/weather/ the package
│ ├── __init__.py ```bash
│ └── constants.py every constant of the lectures python -m pytest
├── tests/ pytest tests (conftest.py runs every test in a python -m ruff check src tests
│ temporary folder) python -m ruff format --check src tests
├── Doxyfile source documentation settings python -m mypy
├── LICENSE ```
├── pyproject.toml project configuration
└── README.md ## Continuous integration
```
`.gitea/workflows/ci.yml` runs on Gitea Actions on every push and on every pull
## License request. It sets up Python 3.13, upgrades `pip`, installs `.[dev]`, then runs
`pytest`, `ruff` (lint and format check) and `mypy`. It does not build the source
GNU Affero General Public License v3.0 only. See [LICENSE](LICENSE). documentation: run `doxygen Doxyfile` yourself, as the next section shows.
The workflow lives in `.gitea/workflows` and not in `.github/workflows`, so
GitHub does not run it and pushing to a GitHub mirror needs no workflow
permission.
## Build the source documentation
The source is documented with Doxygen comments and the `Doxyfile` in the root.
Install Doxygen (`winget install DimitriVanHeesch.Doxygen` on Windows,
`sudo apt install doxygen` on Debian, `brew install doxygen` on macOS), then:
```bash
doxygen Doxyfile
```
The HTML is written to `build/doxygen/index.html`. A warning fails the build.
## Project layout
```text
.
├── .gitea/workflows/ci.yml continuous integration (Gitea Actions)
├── docs/ business case, plan, milestones, reviews, screenshot
├── src/weather/ the package
│ ├── __init__.py
│ ├── __main__.py prints the results: python -m weather
│ ├── analysis.py read_data, average_temp, max_temp, row selection (pandas)
│ ├── constants.py every constant of the lectures
│ ├── csv_reader.py read_rows and read_temperatures (csv library)
│ ├── export.py create_scores_frame and export_frame (pandas)
│ └── weather_data.csv the weather data of the lecture
├── tests/ pytest tests (conftest.py runs every test in a
│ temporary folder)
├── wiki/ wiki pages in English, Danish and Bahasa Melayu
├── Doxyfile source documentation settings
├── LICENSE
├── pyproject.toml project configuration
└── README.md
```
## License
GNU Affero General Public License v3.0 only. See [LICENSE](LICENSE).