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Climate-Data-Analysis-CyL-using-python-

This will be a diary of my Final Year Project (TFG) in Physics. I will upload my working method and my python scripts that I use in the data analysis from AEMET and Inforiego to see if climate change is notable in this region of Spain.

❓About the Project

The goal of this project is to collect, clean and analyze historical meteorological data to see if climate change is appreciable in Castilla y Leon, Spain. The principal purpose is to understand whether precipitacion has varied over the years in this region.

📕Work Diary

Until now I made this work:

  1. Geographical analysis: I selected 3 or 4 meteorological stations well separated to fully analyze each province of Castilla y Leon as best as possible.

  2. Download data (API): I downloaded the data from different meteorological stations using AEMET API in a scale of 30-45 years (from 1980 to 2025).

  3. Data cleaning and analysis: I developed a script to identify the missing data (days or years) for each station and then another script to make a massive clean for all the data. Removing corrupted data, making a full daily calendar using dataframes. Libraries used: os, glob and pandas.

  4. Download lost data (API): I downloaded the lost data (API failures, connection drops). And I merged those CSVs with the original datasets.

  5. Data enrichment by using Inforiego: I got new data for the stations(or near them up to a maximum of 25 km to have precise accuracy). I cleaned this new data, transformed the CSVs to match the AEMET format and merged it all in the calendar by using dataframes.

  6. Interpolation: I made a linear interpolation to fill small gaps by the strict 3-day limit. (THIS COULD CHANGE BECAUSE INTERPOLATING PRECIPITATION IS NOT STANDARD SCIENTIFIC PRACTICE).

  7. Visualization: Generating graphs by using matplotlib.pyplot to see the results of temperature and precipitation.

🌧️Structure (Scripts)

Here is a summary of how the python scripts I made work:

1descargaAPI.py: This program accesses to the AEMET API and downloads the data for the station or stations we want. It downloads the data in a time period we indicate. Also it prepares the data into float format and changes commas into dots.

2pruebanalisis.py: This script makes a calendar for our data and tells us the days in which data is missing. Using os and pandas.

3limpiezamasiva.py: Cleans all the data for the different provinces using pandas, glob and os. (corrupt data and other cases).

4analisismasivo.py: It takes the cleaned data and tells us ALL the gaps and the failures by analyzing each year.

5fusion.py: It takes the saved years ("rescates") and the original datasets and merges them into one unique file for each station (CSV).

6inforiego.py: As the name says, this program analyzes the CSVs downloaded from inforiego and converts them into AEMET format. It also cleans this data.

7union.py: It makes the union of AEMET files and Inforiego ones into one unique CSV for each station.

8interpolador.py: Here, we do the linear interpolation with the limit I detailed before.

9grafica.py: This script generates two graphs for each CSV to analyze precipitation and temperature correctly.