Pandas合并不同DataFrame时如何仅保留指定需要的列

你可以通过两种方式调整，实现仅保留expeditions的month列的需求：

方法1：合并前裁剪expeditions数据集（更高效，推荐） #

合并前仅保留expeditions中用于关联的expedition_id列和需要的month列，再执行合并操作，不会引入多余字段。
调整后的完整代码：

import pandas as pd 

members = pd.read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-09-22/members.csv")
expeditions = pd.read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-09-22/expeditions.csv")

# 提前裁剪expeditions，仅保留关联键和需要的month列
expeditions_selected = expeditions[['expedition_id', 'month']]
df_members_expeditions = pd.merge(members, expeditions_selected, on='expedition_id', how='inner')
df_members_expeditions

方法2：合并后筛选需要的列 #

如果已经完成合并，可以直接过滤保留members全部列+expeditions的month列：

import pandas as pd 

members = pd.read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-09-22/members.csv")
expeditions = pd.read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-09-22/expeditions.csv")

df_members_expeditions = pd.merge(members, expeditions, on='expedition_id', how='inner')
# 筛选保留所有members的列 + month列
df_members_expeditions = df_members_expeditions[[*members.columns, 'month']]
df_members_expeditions

内容的提问来源于stack exchange，提问作者user17501078