Question

我目前正在尝试比较两个CSV文件，以检查file1.csv的第一列中的IP地址是否使用Python 3.6在file2.csv中的一行中。如果地址在file2中，我需要将该行的第二列值复制到与文件1相同的新文件中。两个文件设置如下所示：

文件1：

XX.XXX.XXX.1,Test1
XX.XXX.XXX.2,Test2
XX.XXX.XXX.3,Test3
XX.XXX.XXX.4,Test4
XX.XXX.XXX.5,Test5
XX.XXX.XXX.6,Test6
XX.XXX.XXX.7,Test7
XX.XXX.XXX.8,Test8

and so on

文件2：

XX.XXX.XXX.6, Name6
XX.XXX.XXX.7, Name7
XX.XXX.XXX.8, Name8

我需要将result.csv文件看起来像这样：

XX.XXX.XXX.1,Test1, Not found
XX.XXX.XXX.2,Test2, Not found
XX.XXX.XXX.3,Test3, Not found
XX.XXX.XXX.4,Test4, Not found
XX.XXX.XXX.5,Test5, Not found
XX.XXX.XXX.6,Test6,Name6
XX.XXX.XXX.7,Test7,Name7
XX.XXX.XXX.8,Test8,Name8

我到目前为止的代码如下：

import csv

f1 = open('file1.csv', 'r')
f2 = open('file2.csv', 'r')
f3 = open('results.csv', 'w')

c1 = csv.reader(f1)
c2 = csv.reader(f2)
c3 = csv.writer(f3)

file2 = list(c2)

for file1_row in c1:
    row = 1
    found = False
    for file2_row in file2:
        results_row = file1_row
        x = file2_row[3]
        if file1_row[1] == file2_row[1]:

        results_row.append('Found. Name: ' + x)
        found = True
        break
    row += 1
if not found:
    results_row.append('Not found in File1')
c3.writerow(results_row)

f1.close()
f2.close()
f3.close()

现在这段代码正在检查相同的行而不是值。这意味着它不匹配任何东西，因为它要求IP列和相邻列在两个文件上都相同，此外它匹配文件的第1行，第2行，第3行等等，但我需要它来搜索一个在另一个中找到匹配项，而不是按索引比较行。

Answer 1

熊猫解决方案：

import pandas as pd

df1 = pd.read_csv('file_1.csv', names=['a', 'b'])
df2 = pd.read_csv('file_2.csv', names=['a', 'b'])
merged = pd.merge(df1, df2, on='a', how='outer')
merged.to_csv('results.csv', header=False, index=False, na_rep='Not found')

results.csv的内容：

XX.XXX.XXX.1,Test1,Not found
XX.XXX.XXX.2,Test2,Not found
XX.XXX.XXX.3,Test3,Not found
XX.XXX.XXX.4,Test4,Not found
XX.XXX.XXX.5,Test5,Not found
XX.XXX.XXX.6,Test6, Name6
XX.XXX.XXX.7,Test7, Name7
XX.XXX.XXX.8,Test8, Name8

Answer 2

我移动了results_row的位置并在行+ = 1

之后更改了缩进

import csv

f1 = open('file1.csv', 'r')
f2 = open('file2.csv', 'r')
f3 = open('results.csv', 'w')

c1 = csv.reader(f1)
c2 = csv.reader(f2)
c3 = csv.writer(f3)

file2 = list(c2)

for file1_row in c1:
    row = 1
    found = False
    results_row = file1_row  #Moved out from nested loop
    for file2_row in file2:        
        x = file2_row[1]
        if file1_row[0] == file2_row[0]:
            results_row.append(x)
            found = True
            break
    row += 1
    if not found:
        results_row.append('Not found')     
    c3.writerow(results_row)

f1.close()
f2.close()
f3.close()

Answer 3

您尝试过的解决方案如下：

with open('result.csv', 'w') as out:
    with open('file1.csv', 'r') as f1, open('file2.csv', 'r') as f2:
        f2_lines = [line for line in f2.readlines() if len(line) > 1]
        f1_lines = [line for line in f1.readlines() if len(line) > 1]
        for line in f1_lines:
            val = 'Not found'
            b = [line.split(',')[0].strip() in item for item in f2_lines]
            if any(b):
                val = f2_lines[b.index(True)].split(',')[1].strip()
            out.write('{}, {}\n'.format(line.strip(), val))

<强>输出：

XX.XXX.XXX.1,Test1, Not found
XX.XXX.XXX.2,Test2, Not found
XX.XXX.XXX.3,Test3, Not found
XX.XXX.XXX.4,Test4, Not found
XX.XXX.XXX.5,Test5, Not found
XX.XXX.XXX.6,Test6, Name6
XX.XXX.XXX.7,Test7, Name7
XX.XXX.XXX.8,Test8, Name8

Answer 4

这是一个非熊猫的解决方案（假设您使用的是Python 3.x）：

import csv

present = {}
with open('file2.csv', 'r', newline='') as file2:
    reader = csv.reader(file2, skipinitialspace=True)
    for ip, name in reader:
        present[ip] = name

with open('file1.csv', 'r', newline='') as file1, \
     open('results.csv', 'w', newline='') as results:
    reader = csv.reader(file1, skipinitialspace=True)
    writer = csv.writer(results)
    for ip, name in reader:
        writer.writerow([ip, name, present.get(ip, ' Not found')])

档案Results.csv：

XX.XXX.XXX.1,Test1, Not found
XX.XXX.XXX.2,Test2, Not found
XX.XXX.XXX.3,Test3, Not found
XX.XXX.XXX.4,Test4, Not found
XX.XXX.XXX.5,Test5, Not found
XX.XXX.XXX.6,Test6,Name6
XX.XXX.XXX.7,Test7,Name7
XX.XXX.XXX.8,Test8,Name8

使用两个CSV文件中的匹配列值来创建包含组合数据的新文件

4 个答案: