File:Suomen koronavirus epidemia paivittaiset tapaukset ja kuolemat kevat 2020 1.svg
Original file (SVG file, nominally 877 × 453 pixels, file size: 51 KB)
Captions
Summary
[edit]DescriptionSuomen koronavirus epidemia paivittaiset tapaukset ja kuolemat kevat 2020 1.svg |
English: Coronavirus epidemia in Finland during spring 2020. In this plot only from 26th March, first confirmed Covid-19 case in Finland, to third week of May. Red cases, green recovered, black deaths dark red active cases. |
Date | |
Source | Own work |
Author | Merikanto |
Data for this image is downloaded from Gcovid-19 dataset from GitHub
https://datahub.io/core/covid-19/r/countries-aggregated.csv
with script that downloads data and calculates
active casst with two moving averages
Then data is further processed with spreadsheed and visualized with SciDavis
Python script to download and process Finnish covid-19 data from github
- COVID-19 statistics from aggregated data from net site
- with Python
- Input from internet site: cases, recovered, deats.
- Calculates active cases.
- 12.01.2021
- 0000.0001
-
import math as math
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import locale
from datetime import datetime, timedelta
import matplotlib.dates as mdates
from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,
AutoMinorLocator)
def format_func(value, tick_number):
N = int(np.round(value/10))
if N == 0:
return "0"
else:
return r"${0}\pv$".format(N)
- main proge
dfin = pd.read_csv('https://datahub.io/core/covid-19/r/countries-aggregated.csv', parse_dates=['Date'])
countries = ['Finland']
dfin = dfin[dfin['Country'].isin(countries)]
selected_columns = dfin"Date", "Confirmed", "Recovered", "Deaths"
df2 = selected_columns.copy()
df2.to_csv (r'kovadata1.csv', index = True, header=True, sep=';')
df = pd.read_csv(r'kovadata1.csv', delimiter=';')
len1=len(df["Date"])
aktiv2= [None] * len1
for n in range(0,len1-1):
aktiv2[n]=0
dates=df['Date']
rekov1=df['Recovered']
konf1=df['Confirmed']
death1=df['Deaths']
locale.setlocale(locale.LC_TIME, "fi_FI")
dates_a = [datetime.strptime(d,'%Y-%m-%d').date() for d in dates]
spanni=6
rulla = rekov1.rolling(window=spanni).mean()
rulla2 = rulla.rolling(window=spanni).mean()
tulosrulla=rulla2
- print (rulla)
x=np.linspace(0,len1,len1);
for n in range(0,(len1-1)):
rulla2[n]=round(tulosrulla[n],0)
aktiv2[n]=konf1[n]-death1[n]-rulla2[n]
dailycases1= [0] * len1
dailydeaths1= [0] * len1
for n in range(1,(len1-1)):
dailycases1[n]=konf1[n]-konf1[n-1]
if (dailycases1[n]<0): dailycases1[n]=0
for n in range(1,(len1-1)):
dailydeaths1[n]=death1[n]-death1[n-1]
if (dailydeaths1[n]<0): dailydeaths1[n]=0
fig, ax1 = plt.subplots(constrained_layout=True)
ax1.tick_params(axis='both', which='major', labelsize=15)
ax1.set_xlabel('Kuukausi', color='g',size=18)
ax1.set_ylabel('Päivittäiset uudet tapaukset', color='#7f0000',size=18)
ax1.set_title('Koronavirusepidemian 1. aalto Suomessa', color='b',size=22)
ax1.plot(dates_a,dailycases1, linewidth=2.5, color='#7f0000', label="Päivittäiset tapaukset")
ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis
ax2.set_ylabel('Päivittäiset kuolemat', color='black',size=18)
ax2.tick_params(axis='both', which='major', labelsize=15)
ax2.plot(dates_a,dailydeaths1, linewidth=2, color='black',label="Päivittäiset kuolemat")
lines1, labels1 = ax1.get_legend_handles_labels()
lines2, labels2 = ax2.get_legend_handles_labels()
ax2.legend(lines1 + lines2, labels1 + labels2, loc=0, fontsize=16)
plt.show()
plt.savefig('kuva.svg')
for n in range(0,(len1-1)):
luku0=aktiv2[n]
luku1=luku0.astype(float)
if(math.isnan(luku0)):
aktiv2[n]=0
aktiv2[len1-1]=0
aktiv3a = np.array(aktiv2)
- print(aktiv2)
- print(aktiv3a)
aktiv3=aktiv3a.astype(int)
- print(aktiv3)
print(df)
- df.drop(1, axis=1)
df.insert (2, "Daily_Cases", dailycases1)
df.insert (3, "Daily_Deaths", dailydeaths1)
- quit()
df['ActiveEst']=aktiv3
dfout = df'Date', 'Confirmed','Deaths','Recovered', 'ActiveEst','Daily_Cases','Daily_Deaths'
print(dfout)
dfout.to_csv (r'kovadata2.csv', index = True, header=True, sep=';')
Licensing
[edit]- You are free:
- to share – to copy, distribute and transmit the work
- to remix – to adapt the work
- Under the following conditions:
- attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.
File history
Click on a date/time to view the file as it appeared at that time.
Date/Time | Thumbnail | Dimensions | User | Comment | |
---|---|---|---|---|---|
current | 17:13, 2 September 2020 | 877 × 453 (51 KB) | Merikanto (talk | contribs) | Upload | |
17:11, 2 September 2020 | 576 × 432 (635 bytes) | Merikanto (talk | contribs) | Update | ||
15:56, 14 August 2020 | 1,035 × 443 (48 KB) | Merikanto (talk | contribs) | Update | ||
10:33, 4 August 2020 | 1,037 × 437 (48 KB) | Merikanto (talk | contribs) | Correction of layout of image | ||
05:38, 4 August 2020 | 969 × 477 (45 KB) | Merikanto (talk | contribs) | change contents of image | ||
09:16, 24 May 2020 | 1,109 × 612 (40 KB) | Merikanto (talk | contribs) | Uploaded own work with UploadWizard |
You cannot overwrite this file.
File usage on Commons
The following page uses this file:
Metadata
This file contains additional information such as Exif metadata which may have been added by the digital camera, scanner, or software program used to create or digitize it. If the file has been modified from its original state, some details such as the timestamp may not fully reflect those of the original file. The timestamp is only as accurate as the clock in the camera, and it may be completely wrong.
Width | 701.28pt |
---|---|
Height | 362.16pt |