User Guide
Overview
WeatherReport.jl is designed to work within the Julia REPL. Reports are shown either as plots (via UnicodePlots.jl) or as tables (via PrettyTables.jl). Your location is not tracked, therefore, you need to specify a city/town/village or latitude/longitude yourself. Most major locations (population > 500) around the world are supported.
Available functions
WeatherReport.compare_box_humidityWeatherReport.compare_box_rainWeatherReport.compare_box_snowWeatherReport.compare_box_solarWeatherReport.compare_box_tempWeatherReport.compare_box_windspeedWeatherReport.export_to_sqliteWeatherReport.plot_box_humidityWeatherReport.plot_box_rainWeatherReport.plot_box_snowWeatherReport.plot_box_solarWeatherReport.plot_box_tempWeatherReport.plot_box_windspeedWeatherReport.plot_hist_humidityWeatherReport.plot_hist_rainWeatherReport.plot_hist_snowWeatherReport.plot_hist_solarWeatherReport.plot_hist_tempWeatherReport.plot_hist_windspeedWeatherReport.plot_hourly_dustWeatherReport.plot_hourly_hazeWeatherReport.plot_hourly_humidityWeatherReport.plot_hourly_pmWeatherReport.plot_hourly_rainWeatherReport.plot_hourly_snowWeatherReport.plot_hourly_solarWeatherReport.plot_hourly_tempWeatherReport.plot_hourly_windspeedWeatherReport.show_currentWeatherReport.show_dailyWeatherReport.where_am_i
Supported APIs
Exported names
WeatherReport.compare_box_humidity — Functioncompare_box_humidity(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
month::String = "Jan",
num_years::Int64 = 5)Compares the boxplot distribution of relative humidity at 2 meter above ground for a given location (city or lat/long) for a given month across a given number of years.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Mandatory keywords
month::String: Month for which data needs to be compared, e.g. "Jan", "March" etc.num_years::Int64: Number of years across which the data will be compared
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> compare_box_humidity("Dubrovnik", month = "Feb", num_years = 2)
Dubrovnik: Relative humidity comparison for Feb over last 2 years
Timezone: Europe/Zagreb [Weather data by Open-Meteo.com]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ ╷ ┌────────────────┬──────────┐ ╷┃
2021 ┃ ├──────────────────────────────┤ │ ├────────┤┃
┃ ╵ └────────────────┴──────────┘ ╵┃
┃ ╷ ┌───────────────┬──────────────┐ ╷┃
2022 ┃ ├─────────────────┤ │ ├──────────┤┃
┃ ╵ └───────────────┴──────────────┘ ╵┃
┃ ╷ ┌─────────────────────┬────────────┐ ╷┃
2023 ┃ ├─────────────┤ │ ├─────────┤┃
┃ ╵ └─────────────────────┴────────────┘ ╵┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
20 60 100
[%] WeatherReport.compare_box_rain — Functioncompare_box_rain(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
month::String = "Jan",
num_years::Int64 = 5)Compares the boxplot distribution of rain from large scale weather systems of the preceding hour in millimeter [mm] for a given month across a given number of years.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Mandatory keywords
month::String: Month for which data needs to be compared, e.g. "Jan", "March" etc.num_years::Int64: Number of years across which the data will be compared
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> compare_box_rain("Dubrovnik", month = "March", num_years = 3)
Dubrovnik: Rain comparison for March over last 3 years
Timezone: Europe/Zagreb [Weather data by Open-Meteo.com]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃┐ ╷ ┃
2020 ┃├─────────────────────────────────────────────────┤ ┃
┃┘ ╵ ┃
┃┐ ╷ ┃
2021 ┃├───────────────────────────────────────────────────┤ ┃
┃┘ ╵ ┃
┃┐ ╷ ┃
2022 ┃├────────────────────────────────────────────────────────────────────┤ ┃
┃┘ ╵ ┃
┃┐ ╷ ┃
2023 ┃├─────────────────────────────────────────────────────┤ ┃
┃┘ ╵ ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
0 3 6
[mm] WeatherReport.compare_box_snow — Functioncompare_box_snow(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
month::String = "Jan",
num_years::Int64 = 5)Compares the boxplot distribution of snowfall amount for the preceding hour in centimeter [cm] for a given location (city or lat/long) for a given month across a given number of years.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Mandatory keywords
month::String: Month for which data needs to be compared, e.g. "Jan", "March" etc.num_years::Int64: Number of years across which the data will be compared
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> compare_box_snow("Turku", month = "Jan", num_years = 3)
Turku: Snowfall comparison for Jan over last 3 years
Timezone: Europe/Helsinki [Weather data by Open-Meteo.com]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃┐ ╷ ┃
2020 ┃├───────────────────────────────────┤ ┃
┃┘ ╵ ┃
┃┬─┐ ╷ ┃
2021 ┃│ ├─────────────────────────────────┤ ┃
┃┴─┘ ╵ ┃
┃┐ ╷ ┃
2022 ┃├──────────────────────────────────────────────────────────┤ ┃
┃┘ ╵ ┃
┃┐ ╷ ┃
2023 ┃├───────────────────────────────────┤ ┃
┃┘ ╵ ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
0 1 2
[cm] WeatherReport.compare_box_solar — Functioncompare_box_solar(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
month::String = "Jan",
num_years::Int64 = 5)Compares the boxplot distribution of shortwave solar radiation as average of the preceding hour for a given location (city or lat/long) for a given month across a given number of years. This is equal to the total global horizontal irradiation.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Mandatory keywords
month::String: Month for which data needs to be compared, e.g. "Jan", "March" etc.num_years::Int64: Number of years across which the data will be compared
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> compare_box_solar("Chennai", month = "Sept", num_years = 2)
Chennai: Shortwave radiation comparison for Sept over last 2 years
Timezone: Asia/Kolkata [Weather data by Open-Meteo.com]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃┬──────────────────────────┐ ╷ ┃
2021 ┃│ ├──────────────────────────────────────────┤ ┃
┃┴──────────────────────────┘ ╵ ┃
┃┬─────────────────────────────┐ ╷ ┃
2022 ┃│ ├─────────────────────────────────────────┤ ┃
┃┴─────────────────────────────┘ ╵ ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
0 500 1 000
[W/m^2] WeatherReport.compare_box_temp — Functioncompare_box_temp(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
month::String = "Jan",
num_years::Int64 = 5)Compares the boxplot distribution of hourly air temperature [°C] at 2 meter above ground for a given location (city or lat/long) for a given month across a given number of years.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Mandatory keywords
month::String: Month for which data needs to be compared, e.g. "Jan", "March" etc.num_years::Int64: Number of years across which the data will be compared
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> compare_box_temp("Chandigarh", num_years = 5, month = "May")
Chandigarh: Air temp. comparison for May over last 5 years
Timezone: Asia/Kolkata [Weather data by Open-Meteo.com]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ ╷ ┌─────────┬────────┐ ╷ ┃
2018 ┃ ├───────────────┤ │ ├───────────┤ ┃
┃ ╵ └─────────┴────────┘ ╵ ┃
┃ ╷ ┌──────────┬────────┐ ╷ ┃
2019 ┃ ├──────────┤ │ ├───────────────┤ ┃
┃ ╵ └──────────┴────────┘ ╵ ┃
┃ ╷ ┌────────┬───────┐ ╷ ┃
2020 ┃ ├────────────┤ │ ├───────────────┤ ┃
┃ ╵ └────────┴───────┘ ╵ ┃
┃ ╷ ┌───────┬───────┐ ╷ ┃
2021 ┃ ├───────────┤ │ ├─────────────┤ ┃
┃ ╵ └───────┴───────┘ ╵ ┃
┃ ╷ ┌───────┬───────┐ ╷ ┃
2022 ┃ ├───────────┤ │ ├───────────┤ ┃
┃ ╵ └───────┴───────┘ ╵ ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
10 30 50
[°C] WeatherReport.compare_box_windspeed — Functioncompare_box_windspeed(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
month::String = "Jan",
num_years::Int64 = 5)Compares the boxplot distribution of wind speed at 10 meter above ground for a given location (city or lat/long) for a given month across a given number of years.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Mandatory keywords
month::String: Month for which data needs to be compared, e.g. "Jan", "March" etc.num_years::Int64: Number of years across which the data will be compared
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> compare_box_windspeed("Copenhagen", month = "Feb", num_years = 2)
[ Info: More than one match found, showing report for location in row 1.
[ Info: You can select another location by its row index.
2×4 DataFrame
Row │ CITY TIMEZONE LATITUDE LONGITUDE
│ String? String31 Float64 Float64
─────┼────────────────────────────────────────────────────
1 │ Copenhagen Europe/Copenhagen 55.6759 12.5655
2 │ Copenhagen America/New_York 43.8934 -75.6735
Copenhagen: Wind speed comparison for Feb over last 2 years
Timezone: Europe/Copenhagen [Weather data by Open-Meteo.com]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃╷ ┌────┬──────┐ ╷ ┃
2021 ┃├─────────────┤ │ ├─────────────────┤ ┃
┃╵ └────┴──────┘ ╵ ┃
┃╷ ┌──────┬─────┐ ╷ ┃
2022 ┃├────────────────────┤ │ ├──────────────────────┤ ┃
┃╵ └──────┴─────┘ ╵ ┃
┃ ╷ ┌───────┬────────┐ ╷ ┃
2023 ┃ ├───────────┤ │ ├──────────────────────────────────────────┤ ┃
┃ ╵ └───────┴────────┘ ╵ ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
0 30 60
[km/h] WeatherReport.export_to_sqlite — FunctionSaves the hourly historical temperature, rain, snowfall, relative humidity, windspeed and solar data for a given city (between "startdate" and "enddate") to a SQLite database. Each of the weather variable is saved as a separate table. The database itself is saved to the "export" folder in the root of this repository.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.start_date::String: Starting day in ISO8601 date format, e.g. "2023-02-01"end_date::String: Ending day in ISO8601 date format, e.g. "2023-02-25"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> export_to_sqlite("Veldhoven", start_date = "2022-01-01", end_date = "2022-01-31")WeatherReport.plot_box_humidity — Functionplot_box_humidity(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
year::String = "2022")Shows the monthly boxplot distribution of relative humidity at 2 meter above ground for a given location (city or lat/long).
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.year::String: Year for which data needs to be shown, e.g. "2020"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> plot_box_humidity("Dubrovnik", year = "2023")
Dubrovnik: Relative humidity distribution for 2023
Timezone: Europe/Zagreb [Weather data by Open-Meteo.com]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ ╷ ┌────────────┬────────────┐ ╷┃
January ┃ ├────────────────────────┤ │ ├──────────┤┃
┃ ╵ └────────────┴────────────┘ ╵┃
┃ ╷ ┌───────────────────────┬──────────────┐ ╷┃
February ┃ ├───────────────┤ │ ├───────────┤┃
┃ ╵ └───────────────────────┴──────────────┘ ╵┃
┃╷ ┌───────────┬────────┐ ╷ ┃
March ┃├──────────────────────────────────────┤ │ ├───────────┤ ┃
┃╵ └───────────┴────────┘ ╵ ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
30 65 100
[%] WeatherReport.plot_box_rain — Functionplot_box_rain(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
year::String = "2022")Shows the monthly boxplot distribution of rain from large scale weather systems of the preceding hour in millimeter [mm] for a given location (city or lat/long).
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.year::String: Year for which data needs to be shown, e.g. "2020"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> plot_box_rain("Mumbai", year = "2023")
Mumbai: Rain monthly distribution for 2023
Timezone: Asia/Kolkata [Weather data by Open-Meteo.com]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃┐ ╷ ┃
January ┃├──────┤ ┃
┃┘ ╵ ┃
┃╷ ┃
February ┃┤ ┃
┃╵ ┃
┃┐ ╷┃
March ┃├─────────────────────────────────────────────────────────────────────────┤┃
┃┘ ╵┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
0 0.5 1
[mm] WeatherReport.plot_box_snow — Functionplot_box_snow(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
year::String = "2022")Shows the monthly boxplot distribution of snowfall amount for the preceding hour in centimeter [cm] for a given location (city or lat/long).
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.year::String: Year for which data needs to be shown, e.g. "2020"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> plot_box_snow("Tromso", year = "2023")
Tromso: Snowfall monthly distribution for 2023
Timezone: Europe/Oslo [Weather data by Open-Meteo.com]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃┬───┐ ╷ ┃
January ┃│ ├────────────────────────────┤ ┃
┃┴───┘ ╵ ┃
┃┬───┐ ╷ ┃
February ┃│ ├─────────────────────────────────────────────────────────────────┤ ┃
┃┴───┘ ╵ ┃
┃┬─┐ ╷ ┃
March ┃│ ├──────────────────────────────┤ ┃
┃┴─┘ ╵ ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
0 1 2
[cm] WeatherReport.plot_box_solar — Functionplot_box_solar(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
year::String = "2022")Shows the monthly box plot distribution of shortwave solar radiation as average of the preceding hour for a given location (city or lat/long). This is equal to the total global horizontal irradiation.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.year::String: Year for which data needs to be shown, e.g. "2020"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> plot_box_solar("Canberra", year = "2023")
Canberra: Shortwave radiation distribution for 2023
Timezone: Australia/Sydney [Weather data by Open-Meteo.com]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃┌─┬───────────────┐ ╷ ┃
January ┃┤ │ ├──────────────────────┤ ┃
┃└─┴───────────────┘ ╵ ┃
┃┌┬─────────────────┐ ╷ ┃
February ┃┤│ ├───────────────────┤ ┃
┃└┴─────────────────┘ ╵ ┃
┃┬─────────────┐ ╷ ┃
March ┃│ ├─────────────────────┤ ┃
┃┴─────────────┘ ╵ ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
0 1 000 2 000
[W/m^2] WeatherReport.plot_box_temp — Functionplot_box_temp(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
year::String = "2022")Shows the monthly boxplot distribution of hourly air temperature [°C] at 2 meter above ground for a given location (city or lat/long).
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.year::String: Year for which data needs to be shown, e.g. "2020"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> plot_box_temp("Eindhoven", year = "2023")
Eindhoven: Air temp. monthly distribution for 2023
Timezone: Europe/Amsterdam [Weather data by Open-Meteo.com]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ ╷ ┌─────────┬─────────┐ ╷ ┃
January ┃ ├───────────┤ │ ├────────────────┤ ┃
┃ ╵ └─────────┴─────────┘ ╵ ┃
┃ ╷ ┌──────┬─────┐ ╷ ┃
February ┃ ├─────────────────┤ │ ├────────┤ ┃
┃ ╵ └──────┴─────┘ ╵ ┃
┃ ╷ ┌─────────┬───────┐ ╷ ┃
March ┃ ├──────────────┤ │ ├──────────────┤ ┃
┃ ╵ └─────────┴───────┘ ╵ ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
-10 5 20
[°C] WeatherReport.plot_box_windspeed — Functionplot_box_windspeed(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
year::String = "2022")Shows the monthly box plot distribution of wind speed at 10 meter above ground for a given location (city or lat/long).
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.year::String: Year for which data needs to be shown, e.g. "2020"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> plot_box_windspeed("Veldhoven", year = "2023")
Veldhoven: Wind speed distribution for 2023
Timezone: Europe/Amsterdam [Weather data by Open-Meteo.com]
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ ╷ ┌─────────┬──────────┐ ╷ ┃
January ┃ ├───────────────────┤ │ ├──────────────────────────┤ ┃
┃ ╵ └─────────┴──────────┘ ╵ ┃
┃ ╷ ┌──────┬───────────┐ ╷ ┃
February ┃ ├───────────┤ │ ├─────────────────────────────────┤ ┃
┃ ╵ └──────┴───────────┘ ╵ ┃
┃ ╷ ┌────┬─────────────┐ ╷ ┃
March ┃ ├────────────────┤ │ ├──────────────────────────────────┤ ┃
┃ ╵ └────┴─────────────┘ ╵ ┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
0 20 40
[km/h] WeatherReport.plot_hist_humidity — Functionplot_hist_humidity(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
start_date::String = "2023-01-01",
end_date::String = "2023-01-10")Shows the relative humidity at 2 meter above ground for a given city between startdate and enddate.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.start_date::String: Starting day in ISO8601 date format, e.g. "2023-02-01"end_date::String: Ending day in ISO8601 date format, e.g. "2023-02-25"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> plot_hist_humidity("Chennai", start_date = "2022-01-01", end_date = "2022-12-31")
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Chennai from 2022-01-01 to 2022-12-31⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Asia/Kolkata⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
100 ┃⠀⠀⣄⠀⣠⠀⠀⡀⠀⠀⢠⠀⡄⢰⣧⣷⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠀⡀⠀⠀⠀⠀⣠⡀⠀⠀⠀⠀⣀⠀⣠⣠⣴⠀⠀⠀⡀⢀⢀⠀⣦⡀⡀⠀⠀⠀⠀⣿┃
┃⡇⣦⣿⣶⣿⡇⣿⡇⠀⠀⣿⢰⣿⢸⣿⣿⣿⣷⣶⣾⣰⠀⡀⣶⣆⣷⡆⣾⡆⠀⠀⠀⠀⠀⡄⣆⢠⡆⡀⠀⠀⣷⣿⣶⡇⠀⢰⠀⣦⣿⣷⣶⠀⠀⡄⣿⠀⣿⣿⣿⡇⣼⣿⣷⣼⣿⢰⣿⣿⣧⣾⣿⡄⢸⣿┃
┃⣧⣿⣿⣿⣿⣷⣿⡇⠀⡀⣿⣼⣿⢸⣿⣿⣿⣿⣿⣿⣿⣼⣷⣿⣿⣿⣇⣿⣷⡀⠀⠀⡀⢀⣿⣿⣸⣧⣇⠀⣰⣿⣿⣿⣇⠀⢸⣶⣿⣿⣿⣿⣰⡇⡇⣿⣄⣿⣿⣿⣿⣿⣿⣿⣿⣿⣼⣿⣿⣿⣿⣿⣿⣾⣿┃
┃⣿⣿⣿⣿⣿⣿⣿⣿⣶⣿⣿⣿⣿⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣷⡀⠀⡇⢸⣿⣿⣿⣿⣿⠀⣿⣿⣿⣿⣿⠀⣼⣿⣿⣿⣿⣿⣿⣷⣿⣿⣿⣿⣿⣿⣿⣿⡿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿┃
┃⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣧⢰⣧⣼⣿⣿⣿⣿⣿⠀⣿⣿⣿⣿⣿⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⣿⡇⣿⣿⣿⣿⣿⢿⣿⣿⡿⣿┃
┃⣿⣿⣿⢿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣼⣿⣿⣿⣿⣿⣿⣿⡇⣿⣿⣿⣿⣿⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⣿⡇⣿⡿⣿⣿⣿⢸⣿⣿⡇⣿┃
┃⣿⣿⡏⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⣿⣿⣿⣿⢿⣷⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⢿⣿⣿⢿⣿⡇⣿⠁⢻⡇⠉⡿⢻⠀⢹⣿⡇⣿┃
Rel. humidity [%] ┃⣿⢿⡇⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣇⣿⣿⣿⣿⠸⣿⣿⣿⣿⡏⣿⢿⣿⣿⣿⡟⣿⠘⠋⠹⢸⣿⡇⢸⠀⢸⡇⠀⡇⠘⠀⠸⡟⡇⢿┃
┃⠻⢸⠁⢸⣿⢻⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡿⣿⠀⣿⣿⣿⣿⠃⠋⠸⣿⣿⣿⡇⣿⠀⠀⠀⢸⡇⡇⠘⠀⠈⡇⠀⠃⠀⠀⠀⠇⠀⠸┃
┃⠀⠈⠀⢸⣿⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⣿⣿⣿⣿⣿⣿⡏⢿⣿⣿⣿⣿⣿⡟⢿⣿⣿⠉⣿⣿⠘⠇⢸⠀⣿⣿⣿⣿⠀⠀⠀⣿⣿⣿⡇⢸⠀⠀⠀⢸⡇⠇⠀⠀⠀⠇⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠘⠈⠀⢸⢻⡿⢿⣿⣿⡏⣿⣿⣿⡿⢻⣿⡿⠇⣿⣿⣿⣿⢿⣿⠃⢸⣿⣿⣿⣿⣿⠁⠀⣿⣿⠀⢻⡿⠀⠀⠈⠀⣿⣿⣿⠇⠀⠀⠀⠀⣿⣿⠀⠈⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠸⠁⠀⢸⣿⡇⢿⣿⣿⡇⠈⡇⠀⠀⢻⠈⣿⣿⢸⣿⠀⢸⡏⣿⣿⢻⣿⠀⠀⠃⠀⠀⢸⡇⠀⠀⠀⠀⢻⠇⠈⠀⠀⠀⠀⠀⢸⣿⠀⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠘⡿⡟⠀⠀⠁⠀⠀⠀⠀⠁⢻⠀⠁⠀⠘⠀⣿⠉⢸⡏⠀⠀⠀⠀⠀⢸⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠸⣿⠀⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠇⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠘⠀⠀⠀⠀⠀⠋⠀⠈⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢿⠀⠀⠀⠀⠀⠸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
30 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
⠀2022-01-01T00:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2022-12-31T23:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.plot_hist_rain — Functionplot_hist_rain(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
start_date::String = "2023-01-01",
end_date::String = "2023-01-10")Shows the hourly rain from large scale weather systems of the preceding hour in millimeter [mm] for a given city between startdate and enddate.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.start_date::String: Starting day in ISO8601 date format, e.g. "2023-02-01"end_date::String: Ending day in ISO8601 date format, e.g. "2023-02-25"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> plot_hist_rain("Haldwani", start_date = "2022-01-01", end_date = "2022-12-31")
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Haldwani from 2022-01-01 to 2022-12-31⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Asia/Kolkata⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
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20 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
Rain [mm] ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠀⢸⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⢸⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⢸⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠀⠀⠀⠀⠀⠀⠀⠀⢸⡆⣸⠀⠀⠀⢠⢸⡇⠀⡆⡄⠀⠀⠀⠀⠀⡄⢸⠀⠀⣼⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⡇⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⢸⡇⣿⠀⢸⠀⢸⢸⣇⠀⡇⡇⠀⠀⠀⠀⡀⣷⣸⠀⠀⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⡀⠀⠀⢰⠀⢠⡇⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣄⠀⢸⠀⠀⡆⠀⠀⠀⠀⠀⢸⣿⣿⢠⢸⣇⢸⣿⣿⢰⡇⣷⡇⣦⣶⢀⣿⣿⣿⠀⠀⣿⡆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
0 ┃⣸⣷⣆⣀⣾⣀⣸⣇⣇⣀⣀⣆⣀⣀⣀⣠⣀⣀⣀⣀⣀⣇⣸⣀⣠⣿⣿⣸⣤⣆⣧⣀⣀⣀⣤⣀⣿⣿⣿⣿⣾⣿⣾⣿⣿⣿⣇⣿⣧⣿⣿⣼⣿⣿⣿⣆⣶⡟⣇⣰⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀┃
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⠀2022-01-01T00:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2022-12-31T23:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.plot_hist_snow — Functionplot_hist_snow(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
start_date::String = "2023-01-01",
end_date::String = "2023-01-10")Shows the snowfall amount for the preceding hour in centimeter [cm] for a given location (city or lat/long).
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.start_date::String: Starting day in ISO8601 date format, e.g. "2023-02-01"end_date::String: Ending day in ISO8601 date format, e.g. "2023-02-25"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> plot_hist_snow("Tromso", start_date = "2022-01-01", end_date = "2022-12-31")
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Tromso from 2022-01-01 to 2022-12-31⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Europe/Oslo⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
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3 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⡆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⣧⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
Snowfall [cm] ┃⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⠀⢰⠀⠀⠀⢸⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⢸⣿⢠⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⢸⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣷⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀┃
┃⠀⠀⣿⣿⢸⠀⠀⠀⠀⠀⠀⢸⡀⠀⠀⢸⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⡀⠀⡆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⢀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀┃
┃⡀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠀⢸⡇⡄⠀⢸⢸⠀⠀⠀⠀⠀⠀⢠⢸⠀⡇⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⢀⠀⠀⢸⠀⠀⠀⠀⣼⠀⠀⠀⣄⡀┃
┃⡇⡄⣿⣿⣿⠀⠀⠀⡀⠀⠀⣿⣧⡇⠀⢸⣾⠀⠀⠀⠀⢀⠀⢸⢸⢸⣧⢀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⢸⠀⠀⢸⠀⠀⠀⠀⣿⠀⢀⠀⣿⡇┃
┃⣷⣧⣿⣿⣿⣤⠀⡄⡇⡆⠀⣿⣿⡇⡀⢸⣿⣦⣰⠀⠀⣾⠀⢸⣾⣼⣿⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡀⢀⣿⣼⡆⢀⢸⠀⠀⠀⢰⣿⠀⢸⣄⣿⡇┃
0 ┃⣿⣿⣿⣿⣿⣿⣆⣷⣷⣇⣀⣿⣿⣷⣇⣸⣿⣿⣿⣄⣶⣿⣀⣾⣿⣿⣿⣼⣇⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣇⣸⣿⣿⣇⣸⣸⣀⣀⣀⣸⣿⣀⣾⣿⣿⣿┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
⠀2022-01-01T00:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2022-12-31T23:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.plot_hist_solar — Functionplot_hist_solar(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
start_date::String = "2023-01-01",
end_date::String = "2023-01-10")Shows the shortwave solar radiation as average of the preceding hour for a given location (city or lat/long) between startdate and enddate. This is equal to the total global horizontal irradiation.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.start_date::String: Starting day in ISO8601 date format, e.g. "2023-02-01"end_date::String: Ending day in ISO8601 date format, e.g. "2023-02-25"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> plot_hist_solar("Veldhoven", start_date = "2022-01-01", end_date = "2022-12-31")
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Veldhoven from 2022-01-01 to 2022-12-31⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Europe/Amsterdam⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
900 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠀⠀⠀⠀⠀⢠⡆⡀⢀⠀⠀⠀⢀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⢀⡀⡆⣸⣿⢸⠀⡆⡄⢸⠀⣼⡇⣇⢸⠀⠀⢠⣾⣷⣆⡀⠀⣀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣿⣇⡇⣿⣿⣼⡇⡇⣷⣾⠀⣿⡇⣿⢸⣄⠀⢸⣿⣿⣿⣇⣶⣿⡇⠀⢀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣰⢸⣿⣿⣿⣿⣿⣿⡇⡇⣿⣿⣆⣿⣷⣿⢸⣿⡆⢸⣿⣿⣿⣿⣿⣿⡇⠀⢸⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⣼⣿⢀⣸⣿⣼⣿⣿⣿⣿⣿⣿⡇⣇⣿⣿⣿⣿⣿⣿⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣇⣴⣾⣦⣷⡄⡆⠀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣠⣄⢸⣿⣿⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣇⣿⣿⣿⣿⣿⣿⣿⣼⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⡇⡀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⣾⣿⣿⢸⣿⣿⣾⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⡇⡇⣿⢸⢸⣤⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
Shortwave radiation [W/m^2] ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⣾⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣧⣇⣷⣿⢸⣾⣿⡇⣴⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⢸⣤⣸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⣿⠀⠀⢀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⢀⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⣿⠀⣀⣼⡄⣄⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⢸⢠⡇⣼⢸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⣿⣸⣿⣿⡇⣿⣷⢠⡄⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⣶⣿⢀⣾⢸⡇⣿⣸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡇⣿⣿⣿⣿⣇⣿⣿⣸⣷⠀⡀⢰⣿⠀⠀⡄┃
┃⣧⣿⣿⣼⣿⣸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⢠⣿⣸⣿⣇⣄⣧┃
┃⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿┃
0 ┃⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
⠀2022-01-01T00:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2022-12-31T23:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.plot_hist_temp — Functionplot_hist_temp(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
start_date::String = "2023-01-01",
end_date::String = "2023-01-10")Shows the hourly air temperature [°C] at 2 meter above ground and 'feels like' temperature for a given city between startdate and enddate.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.start_date::String: Starting day in ISO8601 date format, e.g. "2023-02-01"end_date::String: Ending day in ISO8601 date format, e.g. "2023-02-25"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> plot_hist_temp("Veldhoven", start_date = "2022-01-01", end_date = "2022-12-31")
⠀⠀⠀⠀⠀⠀Veldhoven: min -5.9 °C, max 36.4 °C from 2022-01-01 to 2022-12-31)⠀⠀⠀⠀⠀
⠀Timezone: Europe/Amsterdam⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
36.4 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃ Air temperature
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢰⢠⠀⠀⠀⠀⢸⡇⡀⠀⡄⢠⡄⠀⣾⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃ Feels like
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡀⠀⠀⠀⠀⠀⣼⢸⠀⠀⠀⢰⢸⡇⡇⢠⡇⢸⣇⠀⣿⠀⢸⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢰⡇⠀⠀⢀⠀⠀⣿⣼⢰⡀⠀⣸⢸⣿⣇⣾⡇⣿⣿⣴⣿⢀⣿⡇⣠⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⣿⣼⣇⡇⠀⢸⢠⣤⣿⣿⣾⣷⣠⣿⣼⣿⣿⣿⣿⣿⣿⣿⣿⣼⣿⣇⣿⠀⠀⠀⠀⡀⠀⠀⠀⢠⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠀⠀⠀⢸⠀⡀⠀⠀⢸⣿⣿⣿⣷⢠⣾⣾⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⠀⣀⠀⢀⡇⡀⣀⣤⣼⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣠⠀⣾⣶⠀⠀⢸⣷⣷⣇⣼⣿⣿⣿⣿⣿⣾⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⢻⢿⣿⢻⡿⠛⣿⢻⣿⣿⣿⣿⣠⣿⣀⣾⣷⣇⣿⣿⣿⣧⠀⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠┃
[°C] ┃⡆⠀⠀⠀⠀⠀⠀⠀⠀⢠⠀⠀⠀⢠⣿⣧⣿⣿⡆⣄⢸⣿⣿⣿⣿⣿⣿⣿⢹⣿⣿⣿⣿⣿⣿⡏⢻⣿⣿⡟⣿⠘⢸⠇⢸⡇⠀⢸⠀⡟⠃⠸⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣆⠀⠀⠀⠀⠀⠀⠀⠀⢸┃
┃⣷⠀⠀⠀⠀⢰⣀⣸⣦⣾⣴⣇⣴⣸⣿⣿⣿⣿⡇⣿⣾⣿⣿⣿⣿⣿⡿⣿⢸⣿⣿⡿⠛⣿⠛⡇⠘⠻⡟⠃⢻⠀⠈⠀⢸⠀⠀⠈⠀⠃⠀⠀⠈⣿⣿⣿⣿⣿⣿⢿⡏⠋⣿⣿⣿⣿⣄⣷⡆⠀⠀⠀⣰⣷⣿┃
┃⣿⣠⠀⣇⣆⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣇⣿⣿⣿⣿⣿⣿⡿⡇⠇⠈⠿⣿⡇⠀⠸⠀⠃⠀⠀⠀⠀⠈⠀⠀⠀⠈⠀⠀⠀⠀⠀⠀⠀⠀⢻⡟⣿⢻⢻⡟⢸⠁⠀⠹⣿⢿⣿⣿⣿⣷⢀⠀⠀⣿⣿⣿┃
┃⢻⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⡿⢿⣿⠃⠁⠀⠀⠀⠁⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠁⢻⠀⢸⡇⠈⠀⠀⠀⡟⢸⡟⣿⣿⢻⣸⡆⠀⡿⢻⣿┃
┃⣸⣿⣿⣿⣿⣿⣇⣿⣿⣟⣿⣿⣿⣿⣇⣿⣿⣿⣿⣿⣿⣹⣃⣘⣙⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣈⣀⣘⣇⣀⣀⣀⣀⣃⣀⣇⣿⣸⣸⣿⣿⣴⣇⣸⣿┃
┃⢸⣿⣿⡟⣿⡏⠇⠻⢻⠀⢿⣿⢿⣿⠇⢸⠟⠀⣿⡇⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠇⠀⠸⡟⣿⣿⡇⠈⠁┃
┃⠀⠹⠃⠀⠸⠀⠀⠀⠸⠀⠀⢸⠸⣿⠀⠀⠀⠀⢹⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠁⢸⣿⡇⠀⠀┃
-9.8 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠘⣿⡇⠀⠀┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
⠀2022-01-01T00:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2022-12-31T23:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.plot_hist_windspeed — Functionplot_hist_windspeed(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
start_date::String = "2023-01-01",
end_date::String = "2023-01-10")Shows the wind speed at 10 meter above ground for a given city between startdate and enddate.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.start_date::String: Starting day in ISO8601 date format, e.g. "2023-02-01"end_date::String: Ending day in ISO8601 date format, e.g. "2023-02-25"
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)
Example
julia> plot_hist_windspeed("Veldhoven", start_date = "2022-01-01", end_date = "2022-12-31")
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Veldhoven from 2022-01-01 to 2022-12-31⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Europe/Amsterdam⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
60 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⢠⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⡇⠀⠀⢸⣿⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀┃
┃⡄⠀⠀⠀⠀⠀⡇⣶⠀⢸⣿⡆⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣸┃
Wind speed [km/h] ┃⡇⢀⠀⠀⠀⢠⡇⣿⠀⣾⣿⡇⠀⠀⠀⠀⠀⠀⢸⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡄⠀⠀⠀⢠⠀⢀⡄⠀⢠⠀⠀⠀⠀⠀⠀⠀⡀⣿┃
┃⣿⢸⠀⠀⠀⢸⣷⣿⢠⣿⣿⡇⠀⠀⠀⠀⠀⠀⢸⣿⡀⠀⠀⠀⠀⠀⢸⠀⠀⣰⠀⠀⡇⠀⢀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡆⠀⡄⡇⡇⠀⠀⢸⠀⢸⣧⡇⢸⠀⠀⠀⠀⠀⠀⣄⣧⣿┃
┃⣿⣿⠀⠀⡄⣿⣿⣿⣾⣿⣿⡇⠀⠀⡇⣸⡄⠀⣾⣿⡇⠀⢸⡇⠀⠀⢸⡀⣠⣿⡇⢀⡇⠀⢸⠀⠀⡄⣷⡀⠀⡇⡇⣷⢰⠀⠀⠀⠀⠀⠀⢸⠀⡇⠀⡇⡇⡇⠀⠀⢸⡀⣿⣿⡇⢸⢰⡆⢠⠀⠀⠀⣿⣿⣿┃
┃⣿⣿⠀⣷⡇⣿⣿⣿⣿⣿⣿⣿⠀⣸⣿⣿⡇⠀⣿⣿⣧⠀⢸⣧⠀⠀⢸⣿⣿⣿⣧⢸⣷⣰⢸⢀⡆⣿⣿⣷⡀⡇⡇⣿⣼⠀⢀⠀⢰⣸⡀⣿⢠⣿⠀⡇⣿⣧⠀⣧⣿⣇⣿⣿⣿⣾⣸⣧⣸⡄⠀⠀⣿⣿⣿┃
┃⣿⣿⢰⣿⡇⣿⣿⠈⣿⡿⢸⣿⣸⣿⣿⣿⡇⣆⣿⣿⣿⣼⣿⣿⣇⡇⣿⣿⣿⣿⣿⣿⣿⣿⣾⣿⣿⣿⣿⣿⡇⣇⣿⣿⣿⣿⣾⣿⣼⣿⡇⣿⢸⣿⢠⣷⣿⣿⣶⣿⣿⣿⡇⡏⢹⣿⣿⢿⣿⣇⡆⡄⣿⣿⠋┃
┃⣿⣿⣿⣿⢧⣿⣿⠀⣿⠃⠘⣿⣿⣿⣿⣿⣿⣿⣿⡇⣿⣿⡿⣿⣿⣧⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣷⣿⣿⣿⣿⣿⣿⣿⣿⡇⣿⣿⣼⢹⣸⣿⣿⣿⣿⣿⣿⣿⡇⡇⢸⡟⣿⠘⣿⢿⣷⣷⣿⣿⠀┃
┃⢹⠹⡿⣿⢸⡇⢹⠀⠿⠀⠀⢹⡟⡿⢸⣿⣿⢿⢿⠃⣿⡇⠇⢿⢸⣿⡟⣿⣿⡏⠹⣿⠟⢿⢿⢿⣿⢿⣿⣿⣿⣿⠻⡿⣿⠁⣿⣿⣿⡇⢹⣿⣿⠘⣿⢿⢻⠻⣿⣿⠛⢹⡇⡇⢸⠃⡟⠀⡟⢸⣿⣿⢿⢹⠀┃
0 ┃⠀⠀⠃⠸⠸⡇⠀⠀⠀⠀⠀⠸⠁⠀⠀⠁⠟⠸⠀⠀⠟⠃⠀⠀⠸⢹⠇⠁⠀⠁⠀⠻⠀⠈⠘⠸⡏⠘⠏⠸⠘⠹⠀⠇⠁⠀⠻⠛⠏⠀⠸⠃⣿⠀⠋⠸⠈⠀⠃⠘⠀⠘⠃⠁⠈⠀⠃⠀⠁⠈⠏⠹⠀⠈⠀┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
⠀2022-01-01T00:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2022-12-31T23:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀WeatherReport.plot_hourly_dust — Functionplot_hourly_dust(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
days::Int64 = 6)Shows the hourly Saharan dust particles [μg/cm^3] for a given city.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location,
select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)days::Int64: Number of days for which data are returned. Default is 6
days, which is also the maximum.
Example
julia> plot_hourly_dust("Dubai", days = 2)
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Dubai⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Asia/Dubai⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
80 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⢄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡔⠁⠀⠉⢆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠜⠀⠀⠀⠀⠈⢢⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠃⠀⠀⠀⠀⠀⠀⠀⢣⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠓⢄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠤⠔⠒⠊⠉⠉⠒⢄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠜⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠑⠤⣀⠀⠀⠀⠀⠀⣀⡠⠔┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠤⠒⠒⠉⠉⠉⠁⠀⠀⠀⠀⠀⠀⠀⠀⠑⢄⠀⠀⠀⠀⠀⠀⠀⡠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠉⠉⠉⠉⠉⠀⠀⠀┃
dust [μg/m^3] ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠔⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⢆⠀⠀⠀⠀⢀⠎⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠔⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠱⣀⣀⠔⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡔⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠜⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⣀⣀⣀⠤⠤⠤⠤⠊⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
10 ┃⠤⠒⠒⠒⠉⠉⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
⠀2023-03-19T18:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2023-03-21T17:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.plot_hourly_haze — Functionplot_hourly_haze(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
days::Int64 = 6)Shows the hourly Aerosol Optical Depth (AOD) at 550 nm of the entire atmosphere for a given location (city or lat/long). A value of 0.01 corresponds to an extremely clean atmosphere, and a value of 0.4 would correspond to a very hazy condition. (https://gml.noaa.gov/grad/surfrad/aod/)
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location,
select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)days::Int64: Number of days for which data are returned. Default is 6
days, which is also the maximum.
Example
ulia> plot_hourly_haze("Haldwani", days = 2)
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Haldwani⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Asia/Kolkata⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
0.4 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⢣⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠁⠀⠀⠳⡀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠁⠀⠀⠀⠀⠱⡀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣀⣀⣀⣀⡀⠀⠀⠀⠀⠀⣀⣀⠔⠉⠉⠑⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠁⠀⠀⠀⠀⠀⠀⠉⢢⣀⡠⠊┃
Aerosol Optical Depth [] ┃⠤⠤⠤⠤⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠊⠀⠀⠀⠀⠈⠦⠤⠤⠤⠊⠀⠀⠀⠀⠀⠀⠈⢆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠘⠢⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⢆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠈⠢⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⢦⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠎⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠈⠢⠤⠤⡀⠀⠀⠀⠀⠀⢀⠔⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠣⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠎⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠘⠒⠒⠒⠒⠒⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠓⢄⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠑⣄⣀⣀⠀⠀⣀⣀⠔⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠱⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
0.2 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
⠀2023-04-12T17:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2023-04-14T16:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]WeatherReport.plot_hourly_humidity — Functionplot_hourly_humidity(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
days::Int64 = 6)Shows the relative humidity at 2 meter above ground for a given city.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)days::Int64: Number of days for which data are returned. Default is 6 days, which is also the maximum.
Example
julia> plot_hourly_humidity("Veldhoven", days = 3)
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Veldhoven⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Europe/Amsterdam⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
90 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣀⣀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠜⠀⠀⠉⠉⠉⠉⢆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣀⠴⠒⠒⠒⠒⠒⠱⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠁⠀⠀⠀⠀⠀⠀⠀⠈⡆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⡠⠊⠉⠀⠀⠀⠀⠀⠀⠀⠀⢣⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⡠⠔⠊⠉⠢⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠊⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⢱⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⡆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⡔⠁⠀⠀⠀⠀⠈⠦⣀⣀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⡆⠀⠀⠀⠀⠀⠀⠀⠀⠀⡴⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢱⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⢲⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡎⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⢠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠘⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠊┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⡜⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢇⠀⠀⠀⠀⠀⠀⠀⠀⢰⠁⠀┃
Rel. humidity [%] ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠸⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⢀⠇⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢇⠀⠀⠀⠀⠀⠀⠀⠀⡜⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠸⡀⠀⠀⠀⠀⠀⠀⡜⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⢠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⡸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⢠⠃⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⢆⠀⠀⠀⢠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢇⠀⠀⠀⠀⠀⡜⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢱⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠉⠉⠉⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠘⡄⠀⠀⠀⢰⠁⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⡆⠀⠀⠀⠀⢰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠑⠤⢄⡰⠁⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢱⠀⠀⠀⠀⡎⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
40 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠢⣀⣀⡠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
⠀2023-02-25T22:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2023-02-28T21:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.plot_hourly_pm — Functionplot_hourly_pm(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
days::Int64 = 6)Shows the hourly particulate matter [μg/cm^3] with diameter smaller than 10 μm and smaller than 2.5 μm at 10 meter above ground for a given city/location.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)days::Int64: Number of days for which data are returned. Default is 6 days, which is also the maximum.
Example
julia> plot_hourly_pm("Veldhoven", days = 3)
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Veldhoven⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Europe/Amsterdam⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
27.5 ┃⠀⠀⠀⠀⠀⠀⠀⣇⠀⠀⠀⠀⠀⡰⢤⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⣀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃ Part. matter < 10 μm
┃⠀⠀⠀⠀⡖⢇⢰⢹⠀⠀⠀⠀⢰⢱⢤⢇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠁⠀⢣⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃ Part. matter < 2.5 μm
┃⠀⠀⠀⢸⠀⠸⣸⢸⠀⠀⠀⢠⠃⡇⠀⡟⠒⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡜⠀⠀⠀⠀⠈⡆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⡜⠀⠀⠇⠈⡆⠀⢀⠎⢸⠀⠀⢸⠀⢣⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢰⠁⠀⠀⠀⠀⠀⠸⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⢀⠇⢀⡄⠀⠀⡇⠀⡜⢀⠇⠀⠀⠀⡇⠐⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠇⠀⠀⢠⣀⣀⠀⠀⢇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⣀⣔⠥⠔⠁⠘⣄⠀⠣⣰⢁⠜⠀⠀⠀⠀⢣⠀⠘⢆⠀⠀⠀⠀⠀⠀⠀⠀⡼⠀⠀⡠⠃⠀⠀⢣⡀⠸⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⡎⠀⠀⠀⠀⠀⠱⡀⣠⠃⠀⠀⠀⠀⠀⠸⡀⠀⠈⠑⡄⠀⠀⠀⠀⠀⢰⠁⠀⡎⠀⠀⠀⠀⠀⠈⢆⢱⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
[μg/m^3] ┃⡸⠀⠀⠀⠀⠀⠀⠀⠋⠀⠀⠀⠀⠀⠀⠀⠀⠑⢄⠀⠀⠘⡄⠀⠀⠀⢀⠇⠀⡸⠀⠀⠀⠀⠀⠀⠀⠘⢆⢣⠀⠀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⢆⠀⠀⠘⠔⢢⢀⠎⠀⢠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠈⠢⡑⠔⠉⠊⠑⠢⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⢆⠀⠀⠀⠀⠋⡠⠊⠉⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠢⠤⢄⠀⠀⠈⠒⢄⠔⢄⣀⠀⠀⠀⠀⠀⠀⡔⠉⠀⠱⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠉⠢⣀⡠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠑⠢⣀⠀⠀⠀⠀⠀⢣⣀⡠⠤⠔⠊⠀⠀⠀⠀⠉⢢⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠎┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠉⠉⠉⠑⢄⡀⢀⠔⠊⠉⠉⠉⠉⠑⠤⢄⣀⣓⠑⢄⠀⠀⠀⠀⠀⢀⠎⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠱⡘⡄⠀⠀⠀⢀⠎⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠱⡘⢄⣀⡠⠊⠀⠀⠀┃
4.1 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠢⠤⠔⢄⡰⠊⠉┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
⠀2023-03-19T17:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2023-03-22T16:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.plot_hourly_rain — Functionplot_hourly_rain(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
days::Int64 = 6)Shows the hourly rain from large scale weather systems of the preceding hour in millimeter [mm] for a given city.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)days::Int64: Number of days for which data are returned. Default is 6 days, which is also the maximum.
Example
julia> plot_hourly_rain("London", 2, days = 5)
[ Info: More than one match found, showing report for location in row 2.
[ Info: You can select another location by its row index.
6×4 DataFrame
Row │ CITY TIMEZONE LATITUDE LONGITUDE
│ String? String31 Float64 Float64
─────┼────────────────────────────────────────────────────
1 │ London America/Toronto 42.9834 -81.233
2 │ London Europe/London 51.5085 -0.12574
3 │ London America/Chicago 35.329 -93.253
4 │ London America/New_York 37.129 -84.0833
5 │ London America/New_York 39.8865 -83.4483
6 │ London America/Los_Angeles 36.4761 -119.443
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀London⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Europe/London⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
2 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡏⡆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
Rain [mm] ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⢱⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡎⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
0 ┃⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⢦⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⡇⠀⠀⢇⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀┃
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⠀2023-02-25T19:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2023-03-02T18:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.plot_hourly_snow — Functionplot_hourly_snow(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
days::Int64 = 6)Shows the snowfall amount for the preceding hour in centimeter [cm] for a given city.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)days::Int64: Number of days for which data are returned. Default is 6 days, which is also the maximum.
Example
julia> plot_hourly_snow("Tromso", days = 3)
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Tromso⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Europe/Oslo⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
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0.7 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣾⠀⠀⠀⠀⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⡜⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⡇⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
Snowfall [cm] ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡟⡄⠀⠀⠀⡇⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⡇⠀⠀⠀⡇⡇⢀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠇⡇⠀⠀⠀⡇⢸⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⡇⢠⠀⠀⡇⢸⢸⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⡇⣼⠀⠀⡇⢸⢸⢇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⡇⡇⡇⢠⠃⢸⡇⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡜⡆⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⢱⠇⡇⢸⠀⢸⡇⢸⠀⠀⠀⡄⠀⠀⠀⠀⡤⠤⠤⠴⠁⢸⠀⠀⠀⠀┃
0 ┃⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣸⠀⢸⠀⢸⣸⠀⢸⠇⠸⣀⣀⡸⠸⣀⣀⣀⣰⠁⠀⠀⠀⠀⠀⢇⣀⣀⣀┃
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⠀2023-02-25T19:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2023-02-28T18:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.plot_hourly_solar — Functionplot_hourly_solar(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
days::Int64 = 6)Shows the shortwave solar radiation as average of the preceding hour. This is equal to the total global horizontal irradiation
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location,
select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)days::Int64: Number of days for which data are returned. Default is 6
days, which is also the maximum.
Example
julia> plot_hourly_solar("Canberra", days = 3)
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Canberra⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Australia/Sydney⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
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1 000 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠲⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⢀⠔⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠁⠀⠸⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢰⠒⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⡜⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠇⠀⠀⠀⢣⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡎⠀⠘⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⡸⠀⠀⠘⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠘⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠃⠀⠀⠸⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⢀⠇⠀⠀⠀⢇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⢇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⢸⠀⠀⠀⠀⠈⢆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢰⠁⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⢱⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⡎⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡜⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠃⠀⠀⠀⠀⠸⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
Shortwave radiation [W/m^2] ┃⠇⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⢣⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⢇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠸⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡜⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⢱⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⢣⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⢱⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠘⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡜⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⢣⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡜⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⡆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠘⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢣⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢱⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡇┃
0 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠣⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⡜⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠸⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⢆⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⠜⠀┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
⠀2023-02-25T23:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2023-02-28T22:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.plot_hourly_temp — Functionplot_hourly_temp(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
days::Int64 = 6)Shows the hourly air temperature [°C] at 2 meter above ground and 'feels like' temperature for a given city.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)days::Int64: Number of days for which data are returned. Default is 6 days, which is also the maximum.
Example
julia> plot_hourly_temp("Veldhoven", days = 2)
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Veldhoven: min -1.5 °C, max 6.3 °C (air temp)⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Europe/Amsterdam⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
6.3 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠔⠉⠉⠉⠢⢄⠀⠀⠀┃ Air temperature
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⣄⣀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠃⠀⠀⠀⠀⠀⠀⠣⡀⠀┃ Feels like
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠎⠁⠀⠀⠈⠱⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠑⡄┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠜⠁⠀⠀⠀⠀⠀⠀⠑⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠘┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠊⠀⠀⠀⠀⠀⠀⠀⠀⠀⠘⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⢆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡜⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠈⠢⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠢⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⠀⠀⠀⢀⠖⠉⠉⠉⠒⠢⠤⣀⡀⠀┃
[°C] ┃⣀⣀⣈⣑⣲⣤⣄⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣠⣃⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣈⣒⣦⣤⣄⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣀⣠⣃⣀⣀⣜⣁⣀⣀⣀⣀⣀⣀⣀⣀⣉⣢┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠉⠑⠢⢄⣀⠀⠀⠀⠀⠀⠀⠀⢀⠎⠀⠀⠀⠀⠀⠀⠀⣀⠤⠤⠤⠤⢄⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠓⠢⢄⣀⣀⠀⠀⠀⠀⠀⠀⠀⢀⡎⠀⠀⡜⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠉⠉⠒⠒⠢⠤⠤⠊⠀⠀⠀⠀⠀⢠⠔⠉⠀⠀⠀⠀⠀⠀⠣⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠉⠉⠉⠓⠲⠤⠔⠁⠀⠀⢰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⢄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠑⢄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠙⠢⣀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠉⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠑⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠎⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠙⠒⠒⠲⠤⣀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠑⠦⠤⠤⠤⢄⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡜⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠑⠦⣀⠀⠀⠀⠀⠀⠀⠀⠀⡰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠙⠒⠒⠒⠒⠤⠤⠤⢤⣀⣀⠔⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
-5.7 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠉⠒⢤⣀⣀⣀⣀⠴⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
⠀2023-02-25T19:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2023-02-27T18:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.plot_hourly_windspeed — Functionplot_hourly_windspeed(city::String = "",
i_row::Int64 = 1;
lat::Float64 = 0.0,
long::Float64 = 0.0,
days::Int64 = 6)Shows the wind speed at 10 meter above ground for a given city.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Optional keywords
lat::Float64: Geographical WGS84 coordinate of the location (°S < 0, °N > 0)long::Float64: Geographical WGS84 coordinate of the location (°W < 0, °E > 0)days::Int64: Number of days for which data are returned. Default is 6 days, which is also the maximum.
Example
julia> plot_hourly_windspeed("Zurich", days = 3)
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Zurich⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀
⠀Timezone: Europe/Zurich⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀[Weather data by Open-Meteo.com]⠀
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
30 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡜⠢⡄⠀⠀⠀⡆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢰⢣⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢠⠊⠀⠀⠘⠎⢣⡸⢰⠀⠀⠀⠀⠀⠀⣠⠀⠀⠀⠀⡸⢆⡎⠈⠑⡄⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠒⠊⢆⠇⠀⠀⠀⠀⠀⠈⠃⠘⣄⠔⠢⡀⢠⠋⠀⢇⣀⠴⠤⠃⠘⠁⠀⠀⢱⢀⢦⠀⣀⠀⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠇⠀⠀⠈⠀⠀⠀⠀⠀⠀⠀⠀⠀⠁⠀⠀⠉⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠋⠀⠋⠀⠉⢸⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡞⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⡆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⣰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢣⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⡀⠀⠀⠀⠀⠀⠀⡰⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⢆⣀⠤⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
Wind speed [km/h] ┃⢰⢇⠀⢀⣄⣀⠤⠔⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⢆⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⡠⠔⢲⠀⠀⠀⠀⠀┃
┃⢸⠸⡜⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠲⡀⠀⠀⠀⠀⠀⠀⠀⠀⣀⠔⠉⠉⠀⠀⠀⠣⡀⠀⠀⠀┃
┃⡜⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠑⠒⠒⢄⣀⡠⠋⠉⠀⠀⠀⠀⠀⠀⠀⠀⠑⠤⡀⠀┃
┃⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠱⡀┃
┃⠇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠑┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
0 ┃⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀┃
┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
⠀2023-02-25T22:00:00⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀2023-02-28T21:00:00⠀
⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀Time [days]⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ WeatherReport.show_current — Functionshow_current(city::String, i_row::Int64 = 1)Shows the current weather conditions for a given city.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Example
julia> show_current("Lisbon")
[ Info: More than one match found, showing report for location in row 1.
[ Info: You can select another location by its row index.
8×4 DataFrame
Row │ CITY TIMEZONE LATITUDE LONGITUDE
│ String? String31 Float64 Float64
─────┼────────────────────────────────────────────────
1 │ Lisbon Europe/Lisbon 38.7167 -9.13333
2 │ Lisbon America/New_York 39.8609 -83.6352
3 │ Lisbon America/New_York 41.604 -72.0117
4 │ Lisbon America/Chicago 41.9211 -91.3855
5 │ Lisbon America/New_York 44.0315 -70.1045
6 │ Lisbon America/Chicago 46.4416 -97.6812
7 │ Lisbon America/New_York 44.2134 -71.9109
8 │ Lisbon America/New_York 40.772 -80.7681
┌───────────────┬───────────┬────────────┬─────────────┬───────────┬─────────┬─────────┐
│ Timezone │ Elevation │ Wind speed │ Temperature │ Condition │ 🌅 │ 🌆 │
│ [WET] │ [m] │ [km/h] │ [°C] │ [] │ [hh:mm] │ [hh:mm] │
├───────────────┼───────────┼────────────┼─────────────┼───────────┼─────────┼─────────┤
│ Europe/Lisbon │ 48.0 │ 9.1 │ 12.5 │ Clear sky │ 7:18 │ 18:21 │
└───────────────┴───────────┴────────────┴─────────────┴───────────┴─────────┴─────────┘WeatherReport.show_daily — Functionshow_daily(city::String, i_row::Int64 = 1)Shows the daily weather conditions for a given city.
Arguments
city::String: Valid city name, e.g. "Oslo", "Paris", "Amsterdam" etc.i_row::Int64: In case of more than one match for a given location, select the desired timezone by providing the row index from the printed DataFrame. Default is set to 1.
Example
julia> show_daily("Veldhoven")
┌────────────┬────────┬────────┬────────────┬────────────┬───────────┬────────────────┬─────────────┬─────────────────────┐
│ Time │ Min. T │ Max. T │ App. min T │ App. max T │ Prec. sum │ Prec. duration │ Prec. prob. │ Condition │
│ [date] │ [°C] │ [°C] │ [°C] │ [°C] │ [mm] │ [hours] │ [%] │ [] │
├────────────┼────────┼────────┼────────────┼────────────┼───────────┼────────────────┼─────────────┼─────────────────────┤
│ 2023-02-26 │ -1.4 │ 4.9 │ -5.7 │ -0.7 │ 0.0 │ 0.0 │ 0 │ Partly cloudy │
│ 2023-02-27 │ -1.6 │ 6.2 │ -5.1 │ 1.4 │ 0.0 │ 0.0 │ 0 │ Overcast │
│ 2023-02-28 │ -1.1 │ 4.3 │ -5.0 │ -1.3 │ 0.0 │ 0.0 │ 0 │ Partly cloudy │
│ 2023-03-01 │ -2.0 │ 5.3 │ -6.4 │ -0.2 │ 0.0 │ 0.0 │ 0 │ Overcast │
│ 2023-03-02 │ -1.2 │ 6.7 │ -5.1 │ 2.0 │ 0.0 │ 0.0 │ 0 │ Partly cloudy │
│ 2023-03-03 │ -1.1 │ 3.3 │ -4.9 │ -0.3 │ 0.0 │ 0.0 │ 0 │ Depositing rime fog │
│ 2023-03-04 │ -0.8 │ 7.5 │ -3.6 │ 4.7 │ 0.0 │ 0.0 │ 0 │ Fog │
└────────────┴────────┴────────┴────────────┴────────────┴───────────┴────────────────┴─────────────┴─────────────────────┘
Europe/Amsterdam CET
[Weather data by Open-Meteo.com]WeatherReport.where_am_i — Methodwhere_am_i()Shows information about your current location.
Example
julia> where_am_i()
┌──────────┬───────────┬──────────────────┬──────────────┬───────────────┬─────────────┐
│ Latitude │ Longitude │ Timezone │ City │ Region │ Country │
├──────────┼───────────┼──────────────────┼──────────────┼───────────────┼─────────────┤
│ 51.3523 │ 5.4305 │ Europe/Amsterdam │ Valkenswaard │ North Brabant │ Netherlands │
└──────────┴───────────┴──────────────────┴──────────────┴───────────────┴─────────────┘