使用兩個CSV文件中的匹配列值創建一個包含組合數據的新文件

Question

我正在嘗試比較兩個CSV文件，以檢查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，我需要該行復制到一個新的文件，該文件是相同的文件1.兩個文件設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文件看起來像這樣：

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 

我的代碼到目前爲止如下：

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() 

此時此代碼正在檢查相同的行而不是值。這意味着它不會匹配任何內容，因爲它要求兩個文件的IP列和相鄰列都相同，此外它還匹配文件的第1行，第2行，第3行等，但我需要它搜索一個文件在另一箇中查找匹配，不按索引比較行。

Answer 1

我移動results_row和改變的縮進的位置排+ = 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

甲大熊貓溶液：

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

密切溶液後您嘗試的內容如下：

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)) 

輸出：

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

這裏有一個非大熊貓的解決方案（假設你使用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