Python CSV获取特定行数据

Question

这是csv文件

name,country,code
Georgina,Saint Helena,ET
Brooks,Austria,LR
Rosaline,Peru,DZ

如何在不循环整个csv文件的情况下获得特定的行数据？

查找以下语法:如果csv中存在searchName，则提取数据

searchName = 'Brooks'
with open('name.csv', 'r') as file:
  reader = csv.DictReader(file)
  for row in reader:
    if (row['name']) == searchName :
      print(row['name'] + ' >> ' + row['country'])

谢谢

为感兴趣的人更新panda解决方案

import pandas as pd

df = pd.read_csv('a.csv')
select_row = df.loc[df['name'] == 'Brooks']
if select_row.empty:
    print('No records')
else:
    print('Print Record')
    print(select_row.country)

Answer 1

获取第一个实例

search_name = 'Brooks'
with open('name.csv', 'r') as file: 
    output = re.search(f'{search_name}.*', file.read())

row = output.group().split(',')
print(row[0], '>>' ,row[1])

获取所有实例

search_name = 'Brooks'
with open('name.csv', 'r') as file: 
    output = re.findall(f'{search_name}.*', file.read())

for row in output: 
    items = row.split(',')
    print(items[0], '>>' ,items[1])

使用DataFrames

import pandas as pd 

search_name = 'Brooks'
df = pd.read_csv('name.csv')
output = df[df.name == search_name].iloc[0]
print(output['name'], '>>', output['country'])

Answer 2

你可以尝试使用熊猫，让你的生活变得更容易，试试这样的东西：

import pandas as pd

df = pd.read_csv('name.csv')

if df.iloc[5, 6]:
# execute condition
else
# execute another condition

我已经给了你一个提纲，你可以试着用它来解决你的问题。

Answer 3

虽然dataframe似乎是最好的选择，但如果您将csv视为一个简单的文本文件，这应该会对您有所帮助：

searchName = 'Brooks'
with open('name.csv', 'r') as f:
    foo = f.read()

items=re.findall(f"{searchName}.*$",foo,re.MULTILINE)

print(items)

输出：

['Brooks,Austria,LR']