我将如何转向这个DF:
id message_id author_id guild_id has_attachments channel_id created_at
37438 37439 702588325613011054 599221212010512394 322850917248663552 0 520132129103806483 2020-04-22 18:35:10.286
37439 37440 702588325969657876 470642155824873472 322850917248663552 0 373594756116119572 2020-04-22 18:35:10.371
37440 37441 702588327467024474 371187008971866114 322850917248663552 0 362236453771804683 2020-04-22 18:35:10.728
37441 37442 702588328029061150 284428586981523466 322850917248663552 0 338017726394138624 2020-04-22 18:35:10.862
37442 37443 702588328368930876 382261028051877889 322850917248663552 0 338017726394138624 2020-04-22 18:35:10.943
变成这样:
author_id channel_id
guild_id [sum/count] [sum/count]
我假设这些列分别是author_id raw和channel_id raw,但是我将如何处理呢?
我想将此数据帧每行(行)插入influxdb
答案 0 :(得分:1)
类似这样的东西:
V1 V2 V3
A B B
C A C
D A D
A E E
答案 1 :(得分:0)
您可以使用以下代码对各列求和:
df[[col1, col2, etc]].sum()
并进行计数:
df[[col1, col2, etc]].count()
或
[df[col].value_counts() for col in [col1, col2, etc]]
取决于您要做什么。