#Input
{
"street": "ABCS",
"code": "1234"
}
If sizeOf(code)>10 I need to append with street like "ABCD 1234" and remove the code key.
{
"street": "ABCS",
"code": "12345678910"
}
{
"street": "ABCS 12345678910"
}
Like that if sizeOf(code)<10 and street= null. I need to remove street key.
{
"street": null,
"code": "12345"
}
{
"code": "12345"
}
If sizeOf(code)>10 and street = null remove the code key and add the value to street.
{
"street": null,
"code": "12345678910"
}
{
"street": "12345678910"
}
I need to get all these scenarios in single response. Can anyone help me on this.
Regards
Niranjan K
12 de mai. de 2022, 11:44 @Mohammed Abdul Khader Sufi
Thanks for you response.
But I need to verify both the fields. Last condition is not working. If code > 10 and street =null remove code and paste whatever the value coming from code to street.
Is it possible to write down the condition in below similar way.
{
"street": condition,
"code": condition
}
Regards
Niranjan K
Hi Everyone,
Am trying to integrate a python model with a tableau worksheet. I have anaconda and python nstalled and Tabpy is connected and works properly.
SCRIPT_INT("
import pickle
import pandas as pd
import numpy as np
from pandas import Series,DataFrame
filename = 'C:/aaaTENNIS-DATA/votingC.pkl'
loaded_model = pickle.load(open(filename,'rb'))
##input =np.array([[0.7,0.7,0.3,0.3]])
input =np.array([[_arg1,_arg2,_arg3,_arg4]])
Prediction = loaded_model.predict(input)
return 3
",
0.7,0.7,0.3,0.3)
This fails with error message;
An error occurred while communicating with the Analytics Extension.
Error processing script
ValueError : Found array with dim 3. Estimator expected <= 2.
If I try it like this it runs without error, even though it is using the same 4 values .
SCRIPT_INT("
import pickle
import pandas as pd
import numpy as np
from pandas import Series,DataFrame
filename = 'C:/aaaTENNIS-DATA/votingC.pkl'
loaded_model = pickle.load(open(filename,'rb'))
input =np.array([[0.7,0.7,0.3,0.3]])
#input =np.array([[_arg1,_arg2,_arg3,_arg4]])
Prediction = loaded_model.predict(input)
return 3
",
0.7,0.7,0.3,0.3)
Any help appreciated.
Thanks,
Neil.