使用两个CSV文件中的匹配列值创建一个包含组合数据的新文件

Question

我正在尝试比较两个CSV文件，以检查file1.csv的第一列中的IP地址是否在file2.csv的一行中Python 3.6。如果地址是在文件2，我需要该行复制到一个新的文件，该文件是相同的文件1.两个文件设置的第二列的值如下所示：

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 

我需要的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 

我的代码到目前为止如下：

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() 

此时此代码正在检查相同的行而不是值。这意味着它不会匹配任何内容，因为它要求两个文件的IP列和相邻列都相同，此外它还匹配文件的第1行，第2行，第3行等，但我需要它搜索一个文件在另一个中查找匹配，不按索引比较行。

Answer 1

我移动results_row和改变的缩进的位置排+ = 1

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 2

甲大熊猫溶液：

含量 results.csv

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') 

：

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 3

密切溶液后您尝试的内容如下：

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)) 

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

这里有一个非大熊猫的解决方案（假设你使用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')]) 

文件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