我有以下数据框摘要:
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
我想按IP分组,然后使用一些功能进行计数:
1)1分钟内每个IP有多少个唯一CIK
2)在1分钟内每个IP总共有多少CIK。
我已经尝试过重采样功能,但是我不知道如何按照我想要的方式进行计数。 我的代码如下:
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
或者,如果有人可以告诉我如何按IP分组,那么每1分钟,剩下的我可以自己动手。我并不一定要寻找完整的解决方案,请多多指教。