谁能帮我看一下这一段代码什么意思 就两行#号夹起来的那段代码具体解释一下 大概意思能看懂 想知道细节 每一步怎么运作的
因为groupy后的结果他会输出地址而不是数据 我也试过一步一输出 弄不懂
import pandas as pd
def make_item_time_pair(df):
return list(zip(df['click_article_id'], df['click_timestamp']))
dict = {'user_id':[1, 2, 1, 4, 2, 3], 'click_article_id':[4, 5, 6, 4, 5, 6], 'click_timestamp':[8, 6, 2, 9, 7, 2]}
click_df = pd.DataFrame(dict)
click_df = click_df.sort_values('click_timestamp')
###############################
df = click_df.groupby('user_id')['click_article_id', 'click_timestamp'].apply(lambda x: make_item_time_pair(x))\
.reset_index().rename(columns={0: 'item_time_list'})
###############################
print(df)
这是输出的结果
E:/Pycharm Project/A/main.py:33: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.
df = click_df.groupby('user_id')['click_article_id', 'click_timestamp'].apply(lambda x: make_item_time_pair(x))\
user_id item_time_list
0 1 [(6, 2), (4, 8)]
1 2 [(5, 6), (5, 7)]
2 3 [(6, 2)]
3 4 [(4, 9)]
Process finished with exit code 0
