Coronavirus Trend In Spain

April 7, 2020 • edited September 6, 2024

After the video from Minute Earth about the coronavirus, I’ve decided to plot the same data but only for Spain by province. This gives a good view of which provinces are managing to stop the virus.

You have to watch the video to understand the following plots.

Not that your understand… enjoy it.

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Code could not finish, this are some reasons why this happen. - Plot name not defined. The first parameter of the shortcode is the name. - There is a syntax error. check browser console.
Code could not finish, this are some reasons why this happen. - Plot name not defined. The first parameter of the shortcode is the name. - There is a syntax error. check browser console.
Code could not finish, this are some reasons why this happen. - Plot name not defined. The first parameter of the shortcode is the name. - There is a syntax error. check browser console.

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import pandas as pd
import requests
import json

from datetime import timedelta,datetime, date
from io import StringIO


codigos = {'AN':'Andalucía',
'AR':'Aragón',
'AS':'Asturias',
'CN':'Canarias',
'CB':'Cantabria',
'CM':'Castilla-La Mancha',
'CL':'Castilla y León',
'CT':'Cataluña',
'EX':'Extremadura',
'GA':'Galicia',
'IB':'Islas Baleares',
'RI':'La Rioja',
'MD':'Comunidad de Madrid',
'MC':'Región de Murcia',
'NC':'Navarra',
'PV':'País Vasco',
'VC':'Comunidad Valenciana',
'CE':'Ceuta',
'ML':'Melilla'
}


population = pd.read_html("https://es.wikipedia.org/wiki/Anexo:Provincias_y_ciudades_aut%C3%B3nomas_de_Espa%C3%B1a")[0]
population.Población = population.Población.str.replace(".","").astype(int)
population = population.groupby("Comunidad autónoma").sum()["Población"].to_dict()

r = requests.get("https://covid19.isciii.es/resources/serie_historica_acumulados.csv")
text = r.text[0:r.text.index("NOTA")]
spain = pd.read_csv(StringIO(text)).dropna(subset=["CCAA"])
spain.columns =  [c.strip() for c in spain.columns]
spain["Provincia"] = spain["CCAA"].apply(lambda x: codigos[x])
spain["Poblacion"] = spain.Provincia.apply(lambda x: population[x])
spain["Nuevos_Casos"] = spain.groupby("Provincia")["CASOS"].diff()
spain["Casos_x_1000"] = 1000*spain.CASOS / spain.Poblacion
spain["Nuevos_Casos_x_1000"] =  1000* spain.Nuevos_Casos / spain.Poblacion
spain["Nuevos_Casos_Ultima_Semana"] = spain.groupby("Provincia")["Nuevos_Casos"].rolling(7).sum().reset_index(0,drop=True)
spainc = spain[spain.CASOS > 1000]

fig = {
    "data":[ {
        "y":spainc[(spainc["Provincia"]==cat)]["Nuevos_Casos_Ultima_Semana"].to_list(),
        "x":spainc[(spainc["Provincia"]==cat)]["CASOS"].to_list(),
        "text": spainc[(spainc["Provincia"]==cat)]["FECHA"].to_list(),
        "name": cat,
        "mode": "lines+markers"
    } for cat in sorted(spain["Provincia"].unique()) ],
    "layout":{
        "title":"Exito frenando el coronavirus por comunidad",
        "xaxis":{
            "title": "Casos Totales",
            "type":"log"
        },
        "yaxis":{
            "title": "Casos Nuevos Ultima Semana",
            "type":"log"
        }
    }

}
local = json.dumps(fig)


aggregated = spain.groupby(["FECHA"],as_index=False).sum()[["FECHA","CASOS","Nuevos_Casos","Nuevos_Casos_Ultima_Semana"]].sort_values("CASOS")
fig = {
    "data": [{
        "y":aggregated["Nuevos_Casos_Ultima_Semana"].to_list(),
        "x":aggregated["CASOS"].to_list(),
        "name": "casos totales",
        "mode": "lines+markers"
    }],
    "layout":{
        "title":"Exito frenando el coronavirus total",
        "xaxis":{
            "title": "Casos Totales",
            "type":"log"
        },
        "yaxis":{
            "title": "Casos Nuevos Ultima Semana",
            "type":"log"
        }
    }

}
total = json.dumps(fig)


from scipy.optimize import curve_fit
import numpy as np
from numpy import linspace

aggregated["UNIX"] = pd.to_datetime(aggregated["FECHA"],dayfirst=True)

def gauss(x, A,mu,sigma):
    return A*np.exp(-(x-mu)**2/(2.*sigma**2))

p0 = [50000, 40, 5]

popt, pcov = curve_fit(gauss,
                       aggregated.index.to_series(),
                       aggregated['Nuevos_Casos_Ultima_Semana'],
                       p0,
                       method='dogbox')
x = np.linspace(1, 90, 90)
y = gauss(x, *popt)
xdate = pd.Series(x).apply(lambda x: aggregated.UNIX.min() + timedelta(days=x) )
prediction = pd.DataFrame(data={"y":pd.Series(y),"UNIX":xdate})
prediction = prediction[prediction.y > 1]

fig = {
    "data":[ {
        "y":aggregated["Nuevos_Casos_Ultima_Semana"],
        "x":aggregated.UNIX,
        "name": "Nuevos Casos Ultima Semana",
        "mode": "lines+markers"
    },{
        "y":prediction.y,
        "x":prediction.UNIX,
        "name": "prediccion",
        "mode": "lines"
    }  ],
    "layout":{
        "yaxis":{
        }
    }
}
prediction = json.dumps(fig)

template = """

<div class="figure">
<div class="figure-error">


</div>
<div class="figure-plot" id="local_corona">
	Code could not finish, this are some reasons why this happen.
	- Plot name not defined. The first parameter of the shortcode is the name.
	- There is a syntax error. check browser console.
</div>
<script>
  function draw(){
	test = document.getElementById("local_corona");
	if (test == null){
		console.log("The plot name is not defined")
		return
	}

	fig = null
	
	
fig = %s

	

	if (!fig) {
		test.innerText = "ERROR: fig variable is not defined"
		return
	}
	test.innerText = null
	Plotly.plot(test ,fig);
  }
  draw()
</script>
</div>


<div class="figure">
<div class="figure-error">


</div>
<div class="figure-plot" id="total_corona">
	Code could not finish, this are some reasons why this happen.
	- Plot name not defined. The first parameter of the shortcode is the name.
	- There is a syntax error. check browser console.
</div>
<script>
  function draw(){
	test = document.getElementById("total_corona");
	if (test == null){
		console.log("The plot name is not defined")
		return
	}

	fig = null
	
	
fig = %s

	

	if (!fig) {
		test.innerText = "ERROR: fig variable is not defined"
		return
	}
	test.innerText = null
	Plotly.plot(test ,fig);
  }
  draw()
</script>
</div>


<div class="figure">
<div class="figure-error">


</div>
<div class="figure-plot" id="prediction_corona">
	Code could not finish, this are some reasons why this happen.
	- Plot name not defined. The first parameter of the shortcode is the name.
	- There is a syntax error. check browser console.
</div>
<script>
  function draw(){
	test = document.getElementById("prediction_corona");
	if (test == null){
		console.log("The plot name is not defined")
		return
	}

	fig = null
	
	
fig = %s

	

	if (!fig) {
		test.innerText = "ERROR: fig variable is not defined"
		return
	}
	test.innerText = null
	Plotly.plot(test ,fig);
  }
  draw()
</script>
</div>
"""

print(template % (local, total, prediction))

Refer to Add Plots With Hugo Shortcodes if you do not understand the previus template.

References

blogcoronavirus

The Clap Button

2020-03-30 Weekend Learnings