pandas frequency of each entry of a value in a row for a given column

Question

This dataframe is obtained from a timeseries resample operation as shown below

                    Ticket  Priority
Submit Date     
2018-01-02 04:00:00      1  P3 - Normal
2018-01-02 08:00:00     18  P3 - NormalP3 - NormalP3 - NormalP3 - NormalP3...
2018-01-02 12:00:00     23  P2 - HighP3 - NormalP3 - NormalP3 - NormalP3 -...
2018-01-02 16:00:00      1  P3 - Normal
2018-01-02 20:00:00      0  0
2018-01-03 00:00:00      0  0
2018-01-03 04:00:00      1  P3 - Normal
2018-01-03 08:00:00      3  P3 - NormalP3 - NormalP3 - Normal

what I'm looking to get actually is something like this:

                    Ticket  Priority
Submit Date     
2018-01-02 04:00:00      1  P3 - Normal = 1
2018-01-02 08:00:00     18  P3 - Normal = 4
2018-01-02 12:00:00     23  P2 - High   = 1
                            P3 - Normal = 3
2018-01-02 16:00:00      1  P3 - Normal = 1
2018-01-02 20:00:00      0  0
2018-01-03 00:00:00      0  0
2018-01-03 04:00:00      1  P3 - Normal = 1
2018-01-03 08:00:00      3  P3 - Normal = 3

where the Priority column lists the type of ticket and the count of occurrence of each of those ticket types.

Danny · Accepted Answer · 2020-01-16 15:32:27Z

1

def get_priorities(x):
    types = ['Normal','High']
    if x == 0:
         return 0
    else:
        z = []
        for y in types:
            if y in x:
                z.append(str(x[:2]+ '-' + '{} = '.format(y) + str(x.count(y))))
        return ' '.join(z)

This should be your custom function and use lambda to apply it on your data frame.

df['Priority'] = df['Priority'].apply(lambda x: get_priorities(x))

Let me know if this does not work for you.

answered Jan 16, 2020 at 15:32

Danny

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