Pandas-Dataframe: how to count the number of times a variable is repeated in 1 minute

Question

I have the following dataframe snippet:

Full dataframe:                   ip      time      cik  crawler
ts                                                              
2019-03-11 00:00:01   71.155.177.ide  00:00:01  1262327      0.0
2019-03-11 00:00:02   71.155.177.ide  00:00:02  1262329      0.0
2019-03-11 00:00:05   69.243.218.cah  00:00:05   751200      0.0
2019-03-11 00:00:08  172.173.121.efb  00:00:08   881890      0.0
2019-03-11 00:00:09   216.254.60.idd  00:00:09  1219169      0.0
2019-03-11 00:00:09    64.18.197.gjc  00:00:09  1261705      0.0
2019-03-11 00:00:09    64.18.197.gjc  00:00:09  1261734      0.0
2019-03-11 00:00:10    64.18.197.gjc  00:00:10  1263094      0.0
2019-03-11 00:00:10    64.18.197.gjc  00:00:10  1264242      0.0
2019-03-11 00:00:10    64.18.197.gjc  00:00:10  1264242      0.0

I want to group by IPs and then use some function to count:

1) How many unique CIKs are per IP in 1 minute

2) How many CIKs (in total) are per IP in 1 minute.

I have tried the resample function, but I don't know how to make it count in the way I want it. My code is the following:

dataframe = pd.read_csv(path + "log20060702.csv", usecols=['cik', 'ip', 'time', 'crawler'])
dataframe = dataframe[dataframe['crawler'] == 0]
dataframe['cik'] = pd.to_numeric(dataframe['cik'], downcast='integer')
dataframe['ts'] = pd.to_datetime((dataframe['time']))

dataframe = dataframe.set_index(['ts'])
print("Full dataframe: ", dataframe.head(10))

df_dict = dataframe.groupby("ip")
counter = 0
for key, df_values in df_dict:
    counter += 1
    print("df values: ", df_values)
    # df_values = df_values.resample("5T").count()
    if counter == 5:
        break

Or if someone could tell me how can I group by IP and every 1 minute and the rest I can do myself. I'm not looking necessarily for the full solution, some guidance would be much appreciated.

Answer 1

Use groupby with DataFrameGroupBy.resample and aggregate SeriesGroupBy.nunique with count by DataFrameGroupBy.size :

df = dataframe.groupby("ip").resample('1Min')['cik'].agg(['nunique','size'])
print (df)
                            nunique  size
ip              ts                       
172.173.121.efb 2019-03-11        1     1
216.254.60.idd  2019-03-11        1     1
64.18.197.gjc   2019-03-11        4     5
69.243.218.cah  2019-03-11        1     1
71.155.177.ide  2019-03-11        2     2

Or use Grouper:

df = dataframe.groupby(["ip", pd.Grouper(freq='1Min')])['cik'].agg(['nunique','size'])
print (df)
                            nunique  size
ip              ts                       
172.173.121.efb 2019-03-11        1     1
216.254.60.idd  2019-03-11        1     1
64.18.197.gjc   2019-03-11        4     5
69.243.218.cah  2019-03-11        1     1
71.155.177.ide  2019-03-11        2     2