其實pandas就是dataframe,spark里面的是一樣的,有些處理方法可以相互借鑒,也可能會有SQL的一些用法,但今天就事論事,不展開,
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1-統計每個用戶的點擊序列數
先給出一個高大上的操作,這一步很關鍵,
df4=df.groupby('user_id')['item_id'].agg(list)
>>> for u in df4:
print(u,len(u))
[13, 11, 23, 4, 7, 28, 10, 0, 16, 25, 21, 15, 26, 20, 14, 3, 5, 12, 1, 24, 9] 21
[10, 22, 14, 16, 26, 29, 27, 24, 28, 20, 25, 15, 13, 8, 7, 6, 23, 9, 18] 19
[12, 16, 2, 22, 15, 14, 13, 6, 1, 10, 25, 8, 19, 0,
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