python - 基于索引数据框使用 Pandas 创建新的(更详细的)数据框

Question

对于新手问题，我深表歉意，但我很难弄清楚 Pandas 的数据框。我有一个数据框，内容类似于

df_index:
Product    Title
100000     Sample main product
200000     Non-consecutive main sample

我有另一个数据框，其中包含更详细的产品列表，其格式如下

df_details:
Product                    Title
100000                    Sample main product
100000-Format-English     Sample product details
100000-Format-Spanish     Sample product details
100000-Format-French      Sample product details
110000                    Another sample main product
110000-Format-English     Another sample details
110000-Format-Spanish     Another sample details
120000                    Yet another sample main product
120000-Format-English     Yet another sample details
120000-Format-Spanish     Yet another sample details
...
200000                    Non-consecutive main sample
200000-Format-English     Non-consecutive sample details
200000-Format-Spanish     Non-consecutive sample details

我想基于 df_details 创建一个新的数据框，但仅限于 df_index 中出现的产品。理想情况下，它看起来像:

new_df:
Product                    Title
100000                    Sample main product
100000-Format-English     Sample product details
100000-Format-Spanish     Sample product details
100000-Format-French      Sample product details
200000                    Non-consecutive main sample
200000-Format-English     Non-consecutive sample details
200000-Format-Spanish     Non-consecutive sample details

这是我迄今为止尝试过的:

new_df = df_details[df_details['Product'][0:5] == df_index['Product'][0:5]]

这给了我一个错误:

ValueError: Can only compare identically-labeled Series objects

我也尝试过

new_df = pd.merge(df_index, df_details, 
  left_on=['Product'[0:5]], right_index=True, how='left')

这确实给了我一个结果数据集，但不是我想要的类型 - 它不包含带有格式信息的详细信息行。

Answer 1

您应该能够将 .isin() 用作:

new_df = df_details[df_details['Product'].isin(df_index['Product']]

这将执行一个仅查找公共(public)索引的掩码。

编辑:仅当列具有相同的字符串时才有效。要解决这个问题，您可以使用 str.contains() :

import re

# create a pattern to look for
pat ='|'.join(map(re.escape, df_index['Product']))

# Create the mask
new_df = df_details[df_details['Product'].str.contains(pat)]

如果列的格式设置为字符串，则此方法有效。