某电商网站用户行为分析【已脱敏】

用户行为分析

final_data为脱敏后的数据

final_data.head()

	user_id	item_id	behavior_type	user_geohash	item_category	time
0	54007195	79633535	1	NaN	3940	2014-11-24 16
1	136952642	337800294	1	NaN	4830	2014-11-22 12
2	121255158	108926788	1	NaN	1970	2014-11-22 08
3	72256073	144090786	1	NaN	4008	2014-12-09 20
4	65645933	250029185	1	9t4qqgn	2825	2014-11-25 17

data = final_data[['user_id', 'item_id', 'behavior_type', 'time']]
data.head()

	user_id	item_id	behavior_type	time
0	54007195	79633535	1	2014-11-24 16
1	136952642	337800294	1	2014-11-22 12
2	121255158	108926788	1	2014-11-22 08
3	72256073	144090786	1	2014-12-09 20
4	65645933	250029185	1	2014-11-25 17

data.shape

(12256906, 4)

data['date'] = data['time'].map(lambda x:x.split(' ')[0])
data['hour'] = data['time'].map(lambda x:x.split(' ')[1])
data.head()

C:\work\software\Anaconda5.3.0\lib\site-packages\ipykernel_launcher.py:1: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  """Entry point for launching an IPython kernel.

	user_id	item_id	behavior_type	time	date	hour
0	54007195	79633535	1	2014-11-24 16	2014-11-24	16
1	136952642	337800294	1	2014-11-22 12	2014-11-22	12
2	121255158	108926788	1	2014-11-22 08	2014-11-22	08
3	72256073	144090786	1	2014-12-09 20	2014-12-09	20
4	65645933	250029185	1	2014-11-25 17	2014-11-25	17

data.drop(['time'], axis=1, inplace=True)
data.head()