如何从 .csv 文件中提取值并将它们放入数组中？

Question

I am trying to extract values from 2 .csv files using python. From the 1st file I am getting a keyword that would be searched in the 2nd file. After the keyword is found, I am trying to collect values from a different column and put them into an array.

This is what the 1st file looks like ( the one that I'm getting the keyword from ):

Action;ItemID;Title;StartPrice;CustomLabel
Revise;13;some title;990;keyword1
Revise;12;some title;1990;keyword2
Revise;14;some title;2990;keyword3

This is what the second .csv file looks like:

Keyword;Item_Title;Item_Price;Item_Condition;Item_Link
keyword1;title1;59.0;used;link1
keyword1;title2;130.0;used;link2
keyword1;title3;165.0;used;link3
keyword2;title1a;600.0;used;link1a
keyword2;title2a;800.0;used;link2a
keyword2;title3a;899.99;used;link3a
keyword2;title4a;1895.0;new;link4a

I am trying to get the CustomLabel value and search it in the Keyword column in the 2nd file. The goal is to collect the Item_Price values for each keyword value into an array.

So far I've tried this, but it doesn't work since it collect all the Item_Price for every keyword into one array.

This is the code in question:

import csv

prices=[]

with open("1.csv",'r') as file:
    file_reader=csv.DictReader(file,delimiter=';')
    for row in file_reader:
        item=row['CustomLabel']

        with open("1.csv",'r',encoding='utf-8') as file1:
            file_reader1=csv.DictReader(file1,delimiter=';')
            for row1 in file_reader1:
                if item in row1['Keyword']:
                    print(row1['Keyword']+" , "+row1['Item_Price'])
                    price=row1['Item_Price']
                    prices.append(price)
print(prices)

And as you can figure out for yourself I am getting an array with all the prices for all the keywords:

['59.0', '130.0', '165.0', '600.0', '800.0', '899.99', '1895.0']

My question: How do I get an array for each keyword in the file? Does my approach work at all ? Or I need to do something differently? Any suggestions on how to achieve that are welcome. I am using python 3.6.5 and could install any packages if necessary.

Answer 1

numpy's function np.loadtxt does just that. It's well documented here

Alternatively, if keeping track of your columns' titles is important to you, have a look at pandas's pd.read_csv , documented there

Answer 2

You can do it by first creating a dictionary to map each CustomLabel to a list of Item_Price s from the second file and then using that dictionary to extract them from the Keyword column in the second file

import csv

prices = {}

with open("1.csv", 'r') as file:
    for row in csv.DictReader(file, delimiter=';'):
        custom_label = row['CustomLabel']
        if custom_label not in prices:
            prices[custom_label] = []

with open("2.csv", 'r', encoding='utf-8') as file:
    for row in csv.DictReader(file, delimiter=';'):
        keyword = row['Keyword']
        if keyword in prices:
            prices[keyword].append(row['Item_Price'])

from pprint import pprint
pprint(prices)

Output:

{'keyword1': ['59.0', '130.0', '165.0'],
 'keyword2': ['600.0', '800.0', '899.99', '1895.0'],
 'keyword3': []}