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Weather Data (Day 25)
Reading CSV weather data in Python. 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 weather_data.csv with Python's built-in csv library and collect the temperatures as whole numbers, and then show how the pandas library does the same in one line. A table is a DataFrame and a column of it is a Series; both can be converted to a dictionary and a list, the average and the maximum temperature can be computed, rows can be selected by a condition, and a DataFrame can be created from a dictionary and exported to a CSV file.
python -m weather in a terminal: the csv part first, then the pandas part.
What the program prints
| Part | Result |
|---|---|
csv library |
The rows of the file and the temperatures [12, 14, 15, 14, 21, 22, 24] |
pandas |
The DataFrame, the dictionary and the list of temperatures |
| Statistics | Average 17.43 (by hand and with mean) and maximum 24 |
| Row selection | The row of Monday, the row of the hottest day (Sunday), Monday in Fahrenheit (53.6) |
| Create and export | A DataFrame of students and scores made from a dictionary; written to a file only with --export |
Functions
| Function | Module | Lecture |
|---|---|---|
read_rows, read_temperatures |
weather.csv_reader |
Reading with the csv library |
read_data |
weather.analysis |
pandas.read_csv |
to_data_dict, to_temp_list |
weather.analysis |
to_dict, to_list |
average_temp, average_temp_mean, max_temp |
weather.analysis |
Sum and length, mean, max |
row_for_day, hottest_row, day_in_fahrenheit |
weather.analysis |
Selecting rows |
create_scores_frame, export_frame |
weather.export |
DataFrame from a dictionary, to_csv |
Run
Python 3.13 or newer is needed. The csv part has no runtime dependencies; pandas is an optional extra that the dev extra installs.
git clone https://git.tirsystem.com/Tirsvad-Udemy-100-days-of-code/025-weather.git
cd 025-weather
python -m venv .venv
python -m pip install --upgrade pip
python -m pip install -e ".[dev]"
python -m weather
Add --export new_data.csv to also write the scores table to a file. The README of the repository has the full set-up for Windows, Linux and macOS.