COVID19
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KeyError: 'Province/State'
Respected Sir,
I tried to run yours filter for my dataset and getting following error while running #import pandas as pd confirmed=pd.merge(confirmed, population,how='left' ,on=['Province/State','Country']) death=pd.merge(death, population,how='left' ,on=['Province/State','Country']) recover=pd.merge(recover, population,how='left' ,on=['Province/State','Country']) confirmed.head()
Could, you please suggest me how to resolve this error
Try to run: confirmed=pd.merge(confirmed, population,how='left' ,on=['Province/State','Country/Region']) and make sure the 'population' df columns name are: Province/State | Country/Region | Population
Respected Sir,
When I tried to run following sub module, after execution it always gives error "division by zero" error. I tried for each input parameter eg. China, Japan, etc of Country/Region column.
`t['1_day_change']=t['3_day_change']=t['7_day_change']=t['1_day_change_rate']=t['3_day_change_rate']=t['7_day_change_rate']=t['last_day']=0
for i in range(1,len(t)):
if(t.iloc[i,1] is t.iloc[i-2,1]):
t.iloc[i,3]=t.iloc[i-1,2]-t.iloc[i-2,2]
t.iloc[i,6]=(t.iloc[i-1,2]/t.iloc[i-2,2]-1)*100
t.iloc[i,9]=t.iloc[i-1,2]
if(t.iloc[i,1] is t.iloc[i-4,1]):
t.iloc[i,4]=t.iloc[i-1,2]-t.iloc[i-4,2]
t.iloc[i,7]=(t.iloc[i-1,2]/t.iloc[i-4,2]-1)*100
if(t.iloc[i,1] is t.iloc[i-8,1]):
t.iloc[i,5]=t.iloc[i-1,2]-t.iloc[i-8,2]
t.iloc[i,8]=(t.iloc[i-1,2]/t.iloc[i-8,2]-1)*100
t=t.fillna(0)
t=t.merge(temp[['date','region', 'X']],how='left',on=['date','region'])
t=t.rename(columns = {'X':'kalman_prediction'})
t=t.replace([np.inf, -np.inf], 0)
t['kalman_prediction']=round(t['kalman_prediction'])
train=t.merge(confirmed[['region',' Population ']],how='left',on='region')
train=train.rename(columns = {' Population ':'population'})
train['population']=train['population'].str.replace(r" ", '')
train['population']=train['population'].str.replace(r",", '')
train['population']=train['population'].fillna(1)
train['population']=train['population'].astype('int32')
train['infected_rate'] =train['last_day']/train['population']*10000
train=train.merge(w,how='left',on=['date','region'])
train=train.sort_values(['region', 'date'])
You should check why you get zero values in t.iloc[,2]. If for some reason you get zeros, you can replace them with the actual values.
Dear Sir,
For the above issue the values of t.tail(7) are highlighted in the following screenshot:
Can you please share yours data set for Confirmed.csv, Deaths.csv and Recovered.csv.
The updated data sets were taken from the following URLs:
url = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv' #url = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv' confirmed = pd.read_csv(url, error_bad_lines=False) #url = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Deaths.csv' url = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv' death = pd.read_csv(url, error_bad_lines=False) url = 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_recovered_global.csv' recover = pd.read_csv(url, error_bad_lines=False)
Dear Sir,
I followed yours valuable suggestion and above errors were resolved.
However, for other different inputs like 'India,' 'Korea, South' the prediction output always gives NAN result. This is shown in the following screenshot
And for Korea, South
Dear Sir, Greeting of the Day !! Please suggest solution for the above issue.
It seems like you don't get predictions from R script. You can share your code with me and I'll try to assist. [email protected]