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Markov model

Import libraries​

from ChannelAttributionPro import *
pd.set_option('display.expand_frame_repr', False)

Set the password​

password="mypassword"

Load data​

Data = pd.read_csv("https://app.channelattribution.net/data/Data.csv",sep=";")

print(Data)

Perform transaction level attribution reading data from a data.frame​

res=markov_model(Data=Data, var_path="path", var_conv="total_conversions", 
                 var_value="total_conversion_value", var_null="total_null", 
                 cha_sep=">", password=password)
path_attribution=res["attribution"]
print(path_attribution)

Return non converting paths in the output data.frame​

res=markov_model(Data=Data, var_path="path", var_conv="total_conversions", 
                 var_value="total_conversion_value",var_null="total_null", 
                 cha_sep=">", flg_write_nulls=1, password=password)
path_attribution=res["attribution"]
print(path_attribution)

Return paths in the output data.frame​

res=markov_model(Data=Data, var_path="path", var_conv="total_conversions", 
                 var_value="total_conversion_value", var_null="total_null", 
                 cha_sep=">", flg_write_paths=1, password=password)
path_attribution=res["attribution"]
print(path_attribution)