用csv模块从csv文件中读取特定的列?

我试图通过csv文件进行解析，并仅从特定列中提取数据。

例csv:

ID | Name | Address | City | State | Zip | Phone | OPEID | IPEDS |
10 | C... | 130 W.. | Mo.. | AL... | 3.. | 334.. | 01023 | 10063 |

我试图只捕获特定的列，比如ID、Name、Zip和Phone。

我看过的代码让我相信我可以通过对应的数字调用特定的列，因此ie: Name将对应于2，并且使用行[2]遍历每一行将产生列2中的所有项。但事实并非如此。

以下是我目前所做的:

import sys, argparse, csv
from settings import *

# command arguments
parser = argparse.ArgumentParser(description='csv to postgres',\
 fromfile_prefix_chars="@" )
parser.add_argument('file', help='csv file to import', action='store')
args = parser.parse_args()
csv_file = args.file

# open csv file
with open(csv_file, 'rb') as csvfile:

    # get number of columns
    for line in csvfile.readlines():
        array = line.split(',')
        first_item = array[0]

    num_columns = len(array)
    csvfile.seek(0)

    reader = csv.reader(csvfile, delimiter=' ')
        included_cols = [1, 2, 6, 7]

    for row in reader:
            content = list(row[i] for i in included_cols)
            print content

我期望它只打印出每行我想要的特定列，但它没有，我只打印出最后一列。

当前回答

从CSV文件读写，您可以导入CSV并使用以下代码:

with open('names.csv', newline='') as csvfile:
    reader = csv.DictReader(csvfile)
    for row in reader:
        print(row['first_name'], row['last_name'])

2022-11-13 18:24:39

其他回答

您可以使用numpy.loadtext(文件名)。例如，如果这是你的数据库。csv:

ID | Name | Address | City | State | Zip | Phone | OPEID | IPEDS |
10 | Adam | 130 W.. | Mo.. | AL... | 3.. | 334.. | 01023 | 10063 |
10 | Carl | 130 W.. | Mo.. | AL... | 3.. | 334.. | 01023 | 10063 |
10 | Adolf | 130 W.. | Mo.. | AL... | 3.. | 334.. | 01023 | 10063 |
10 | Den | 130 W.. | Mo.. | AL... | 3.. | 334.. | 01023 | 10063 |

你需要Name列:

import numpy as np 
b=np.loadtxt(r'filepath\name.csv',dtype=str,delimiter='|',skiprows=1,usecols=(1,))

>>> b
array([' Adam ', ' Carl ', ' Adolf ', ' Den '], 
      dtype='|S7')

你可以更容易地使用genfromtext:

b = np.genfromtxt(r'filepath\name.csv', delimiter='|', names=True,dtype=None)
>>> b['Name']
array([' Adam ', ' Carl ', ' Adolf ', ' Den '], 
      dtype='|S7')

2014-01-10 13:46:04

import pandas as pd

dataset = pd.read_csv('Train.csv')
X = dataset.iloc[:, 1:-1].values
y = dataset.iloc[:, -1].values

X是一堆列，如果你想读更多的列，就用它 Y是单列，用它来读一列 [:， 1:-1]是[row_index: to_row_index, column_index: to_column_index]

2021-11-20 11:21:32

import csv

with open('input.csv', encoding='utf-8-sig') as csv_file:
    # the below statement will skip the first row
    next(csv_file)
    reader= csv.DictReader(csv_file)
   
    Time_col ={'Time' : []}
    #print(Time_col)
    for record in reader :
        Time_col['Time'].append(record['Time'])
        print(Time_col)

2022-08-19 05:00:17

使用熊猫:

import pandas as pd
my_csv = pd.read_csv(filename)
column = my_csv.column_name
# you can also use my_csv['column_name']

在解析时丢弃不需要的列:

my_filtered_csv = pd.read_csv(filename, usecols=['col1', 'col3', 'col7'])

附注:我只是以一种简单的方式汇总其他人说过的话。实际答案是从这里和这里取的。

2017-05-23 09:05:23

Context: For this type of work you should use the amazing python petl library. That will save you a lot of work and potential frustration from doing things 'manually' with the standard csv module. AFAIK, the only people who still use the csv module are those who have not yet discovered better tools for working with tabular data (pandas, petl, etc.), which is fine, but if you plan to work with a lot of data in your career from various strange sources, learning something like petl is one of the best investments you can make. To get started should only take 30 minutes after you've done pip install petl. The documentation is excellent.

答:假设您在csv文件中有第一个表(您也可以使用petl直接从数据库加载)。然后您只需加载它并执行以下操作。

from petl import fromcsv, look, cut, tocsv 

#Load the table
table1 = fromcsv('table1.csv')
# Alter the colums
table2 = cut(table1, 'Song_Name','Artist_ID')
#have a quick look to make sure things are ok. Prints a nicely formatted table to your console
print look(table2)
# Save to new file
tocsv(table2, 'new.csv')

2015-05-29 12:19:22

用csv模块从csv文件中读取特定的列?

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