temp = []
fields = ['error%d' % i for i in range(1,6)]
for col in fields:
temp.append(pd.rolling_sum(pd.pivot_table(error_count,
index='datetime',
columns='machineID',
values=col), window=24).resample('3H',
closed='left',
label='right',
how='first').unstack())
error_count = pd.concat(temp, axis=1)
error_count.columns = [i + 'count' for i in fields]
error_count.reset_index(inplace=True)
error_count = error_count.dropna()
error_count.describe()
How can I calculate the total number of errors of each type in the last 24 hours, for time points taken every three hours? Github has that code, but it is giving this error:
C:Program FilesMicrosoftML
ServerPYTHON_SERVERlibsite-packagesipykernel_launcher.py:7:
FutureWarning: pd.rolling_sum is deprecated for DataFrame and will be
removed in a future version, replace with
DataFrame.rolling(window=24,center=False).sum()
import sys
C:Program FilesMicrosoftML
ServerPYTHON_SERVERlibsite-packagesipykernel_launcher.py:10:
FutureWarning: how in .resample() is deprecated the new syntax is
.resample(...).first() # Remove the CWD from sys.path while we load
stuff.
And I not know how to apply that resolucion.
Link to github: https://github.com/ashishpatel26/Predictive_Maintenance_using_Machine-Learning_Microsoft_Casestudy
I using is version python 3.8
question from:
https://stackoverflow.com/questions/65866008/error-when-using-rolling-sum-on-pandas-how-to-apply-rolling-sum-correctly-t 与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…