This approach provides you with the number of rows and columns in the DataFrame, as well as information about the data type in each column and the number of null values. import pandas as pd # Creating a sample
As you can see, the rules in the 98%+ confidence region appear to be rules that don't really tell us anything. i.e. Birmingham -> West Midlands Police. Let's remove those from the analysis useful_rules_df=rules_df_pd[rules_df_pd['confidence']<0.98]\ .sort_values(by="confidence"...
In below table, we have illustrated the calculation used to arrive at the four measures of dominance.Table 3If we calculate the four measures of dominance from the above example, we will get the following values: Table 4Dominance LevelsThe following three levels of dominance can be achieved ...