Project Work Python and R

Some vital information for everybody is current weather and weather forecast. The project is focusing on weather forecasting in order to make the project done we collect data by accessing the API OpenMeteo. The task is completed when we selected some locations and merged them to have a dataset of 1000 observations, we used R language to complete the task. Then add the code to a GIT repository. The structure of the paper is as follows,variables where we have 25 variables and description of the scripts how the script is working.

Description of the script

The script is based on the building of six different dataset, one for each country that we have selected. First of all, we are going to ask for data with the function GET. After that, through str() you can visualize the raw data and content function gives the possibility of convert the data as a text, in order to make easier work with json data. the fromJSON function will turn that json text string in a more usable R object. glimpse() can help us to get a good look at the structure. Then, as.data.frame() transform the JSON list into a dataframe. We repeat this process for each dataset and, after the building of all of them, with rbind() we merged the datasets together in a single dataset with 1008 observations and 25 variables. In conclusion, we saved the dataset as a .csv file.

API Reference

Get all items

  GET https://api.open-meteo.com/v1/forecast?latitude=52.52&longitude=13.41&hourly=temperature_2m,relativehumidity_2m,dewpoint_2m,apparent_temperature,pressure_msl,precipitation,weathercode,snow_height,freezinglevel_height&timezone={UTC}%2{Location}

Parameter	Unit	Description
temperature_2m	°C (°F)	Air temperature 2 meters above the ground
relativehumidity_2m	%	Relative humidity 2 meters above ground
dewpoint_2m	°C (°F)	Dew point temperature 2 meters above ground
apparent_temperature	°C (°F)	Perceived feel like temperature
pressure_msl	°C (°F)	Atmospheric air pressure reduced to sea level
precipitation	mm (inch)	Sum of the precipitation of the preceding hour
weathercode	WMO Code	weather condition as numeric code
snow_height	meters	Snow height on the ground
freezinglevel_height	meters	Altitude of the 0°C level

Parameter	Format	Description
latitude, longitude	Floating point	Geographical coordinate of the location
hourly_units	object	For each selected weather variable, the unit will be listed here
utc_offset_seconds	iso8601	Applied timezone offset
generation_time	Floating Point	Generation time of the weather forecast in milli seconds
elevation	Floating Point	The elevation in meters of the selected weather grid-cell

Other Documentation

You can find the documentation for task 2 in the two .zip files

Authors

• Enrico Romano(enrico.romano@studenti.luiss.it)
• Khan Gony Jany (Khan.jany@studenti.luiss.it)
• Antonio Marco Vita (antonio.vita@studenti.luiss.it)