使用python从csv解析单个列到文本文件 [英] Parsing out single column from csv into text file using python

问题描述

我终于得到我的dbf文件是一个csv，但现在我很困惑，如何解析为一个文本文件进一步编辑。

一直在读csv模块，但老实说，我的头开始旋转。这么多对我来说似乎是希腊。

我的car.csv文件看起来像这样：

 名称，总数，频率
丰田，2,2 
马自达，1,1 
起亚，2,1 
 Volkswagon， 3,1 
  

我想将以下句子输出到文本文件（或csv） p>

在这个社区内有一辆丰田，马自达，起亚和大众汽车停在街上。

是两个我不想要的逗号：

Cars.dbf

 丰田，2,2 
马自达，2,1 
  

Cars.dbf

 空
  

这个街区内的街道上没有停放的汽车。

我从前一篇文章中得到了一个很好的建议，就是构造if-else语句，但是却失去了如何解析列（由于某种原因，它们没有显示在Excel中，我认为我只有一列）

python 2.7

任何人都知道一个好的网站，解释csv模块在一个总的新手可以理解的术语？感谢。

解决方案

Python文档示例总是一个地方。

你想要这样的：

  import csv 
 
 makes = [] 
 with open（'cars.csv'，'rb'）as f：
 reader = csv.reader（f）
 next（reader）＃忽略第一行
 
读取器中的行：
 makes.append（row [0 ]）
 
 print make 
  

I finally got my dbf file to be a csv but now I am confused as to how to parse this out into a text file for further editing.

I have been reading up on the csv module but to be honest my head began to spin. So much of it seemed Greek to me. However, I would like the code for using module this if possible.

My car.csv file looks like this:

Name,Total,Freq
Toyota,2,2
Mazda,1,1
Kia,2,1
Volkswagon,3,1

I want to output the following sentence into a text file (or csv):

Within this neighborhood there is a Toyota, Mazda, Kia, and Volkswagon parked on the street.

If the results are two I do not want commas:

Cars.dbf

Toyota,2,2
Mazda,2,1

Within this neighborhood there is a Toyota and Mazda parked on the street.

Cars.dbf

empty

There are no cars parked on the street within this neighborhood.

I got a good suggestion from a previous post on constructing the if-else sentences but am lost on how to parse columns (they didn't show up in Excel for some reason, I thought I only had one column)

python 2.7

BTW. Anyone know of a good web site that explains the csv module in terms a total newbie can understand? Thanks.

解决方案

The Python doc examples are always a go to place.

You want something like this:

import csv

makes = []
with open('cars.csv', 'rb') as f:
    reader = csv.reader(f)
    next(reader) # Ignore first row

    for row in reader:
        makes.append(row[0])

print makes

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