Pandas 通过从另一个数据帧的 1 列中的单元格检查列表中返回匹配字符串的行来创建新的数据帧

Question

I have created a dataframe from a .csv with just over 3.8 million rows:

import pandas as pd
import csv

file_name = 'bigfile.csv'
bigfile_df = pd.read_csv (file_name, low_memory=False)

I am then importing a second csv which I would like to be my list:

input_df = pd.read_csv('list.csv', delimiter=',')

Then converting this to a List:

l = input_df['Column_Name'].tolist()

Which when printed looks like:

['Text Text Text', 'Text Text Text', 'Text Text Text']

The list is fairly large as well containing over 12,000 rows and contains strings.

What I would like to do is take each entry within the list and check for any matches within cells from a column ['Name'] in the bigfile_df and create a new dataframe with the entire row of these matches.

I hope this all makes sense, I have looked for similar examples to try and answer this but could not find. Thank you in advance for any replies.

Answer 1

You can achieve this using the query method:

output_dfs = []
for entry in l:
    output_dfs.append(bigfile_df.query('Name == @entry')

Edit: I may have misunderstood, if you want one dataframe you can do as follows:

output_df = bigfile_df.query('Name in @l')

This will search all rows of bigfile_df for rows which have the 'Name' column value appearing in your list l .