BacksGas_Flow_sccm  ContextID   StepID  Time_Elapsed    iso_forest
61.81640625 7289972 19  40.503  -1
62.59765625 7289972 19  41.503  -1
63.671875   7289972 19  42.503  1
65.625  7289972 19  43.503  1
61.81640625 7289973 19  40.448  -1
62.59765625 7289973 19  41.448  -1
63.671875   7289973 19  42.448  1
65.625  7289973 19  43.448  1

def minus1_plus1_ratio(dictionary, new_df, step_df):
    dictionary[new_df] = dictionary[step_df].groupby(['ContextID', 'iso_forest']).size().reset_index(name='count')
    dictionary[new_df] = pd.pivot_table(dictionary[new_df], values = 'count', columns = ['iso_forest'],
                                          index = ['ContextID']).fillna(value = 0)
    dictionary[new_df]['-1/1'] =  (dictionary[new_df][-1])/(dictionary[new_df][1])
    dictionary[new_df] = dictionary[new_df].sort_values(by = '-1/1', ascending = False)
    return dictionary[new_df]

BacksGas_Flow_sccm  ContextID   StepID  Time_Elapsed    iso_forest
61.81640625 7289972 19  40.503  1
62.59765625 7289972 19  41.503  1
63.671875   7289972 19  42.503  1
65.625  7289972 19  43.503  1
61.81640625 7289973 19  40.448  1
62.59765625 7289973 19  41.448  1
63.671875   7289973 19  42.448  1
65.625  7289973 19  43.448  1

dictionary[new_df]['-1/1'] =  (dictionary[new_df][-1])/(dictionary[new_df][1])