如何在python中读取csv文件的特定行？

Question

I have searched like crazy trying to find specifically how to read a row in a csv file.

I need to read a random row out of 1000, each of which has 3 columns. The first column has an email. I need to put in a random email, and get columns 2 and 3 out. (Python 2.7, csv file)

Example:

Name Date  Color
Ray  May   Gray
Alex Apr   Green
Ann  Jun   Blue
Kev  Mar   Gold
Rob  May   Black

Instead of column 1 row 3, I need [Ann], her whole row. This is a CSV file, with over 1000 names. I have to put in her name and output her whole row.

---

What I have tried

from collections import namedtuple
Entry = namedtuple('Entry', 'Name, Date, Color')
file_location = "C:/Users/abriman/Desktop/Book.csv"
ss_dict = {}
spreadsheet = file_location = "C:/Users/abriman/Desktop/Book.csv"
for row in spreadsheet:
    entry = Entry(*tuple(row))
    ss_dict['Ann']

And my error reads

Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
TypeError: __new__() takes exactly 4 arguments (2 given)

I have tried other ways too and got little to no result. I'm a beginner at python.

Answer 1

You're on the right track. First issue: you're never opening the file located at file_location . Thus, when you iterate for row in spreadsheet: , you're iterating over the characters of spreadsheet , which are the characters of file_location , which are the characters of "C:/Users/..." . So the first thing you want to do is actually open the file:

spreadsheet = open(file_location, 'r')

You still have another issue in your loop. When you iterate over a file in a for loop, you get back the lines of the file. So, at each iteration, row will be a line, eg "Ray May Gray" . When you call tuple() on that, you're going to get a tuple that looks like ('R', 'a', 'y', ' ', ' ', 'M', ...) . What you need to do is construct your tuple by splitting on whitespace:

entry = Entry(*row.split())

Then, you need to add your entry to the dictionary ss_dict :

ss_dict[entry.Name] = entry

Finally, you can read out the value of ss_dict['Ann'] , but this should be outside your loop - if you do it inside your loop, you may be trying to read the value of ss_dict['Ann'] before it has been set. All in all, your code should look like this:

from collections import namedtuple
Entry = namedtuple('Entry', 'Name, Date, Color')
file_location = "C:/Users/abriman/Desktop/Book.csv"
ss_dict = {}
spreadsheet = open(file_location, 'r') # <--
for row in spreadsheet:
    entry = Entry(*row.split()) # <--
    ss_dict[entry.Name] = entry # <--
print ss_dict['Ann']

---

Incidentally, the reason you're getting your error message there is that when you do for row in spreadsheet: with spreadsheet being a string, row is just a character , as I mentioned, and so tuple(row) is just a tuple containing one character, and hence is of length 1, so that you're only passing one argument rather than three when you do *tuple(row) .

---

All that said, you might want to consider looking at the csv module , which is part of the standard library, and is precisely designed for reading csv files. It will probably make your life easier in the long run.

Answer 2

I think what you need is enumerate

def read_csv_line(line_number, filename):
    with open("filename.csv") as fileobj
        for i, line in enumerate(fileobj):
            if i == (line_number - 1):
                return line
    return None

Then you can feed your random number and filename to get a random line.

Answer 3

Solution to your problem could be simple dictionary comprehension:

>>> Entry = namedtuple('Entry', 'Name, Date, Color')
>>> [l for l in open('t.tsv', 'r')]
<<<
['Name Date  Color\n',
 'Ray  May   Gray\n',
 'Alex Apr   Green\n',
 'Ann  Jun   Blue\n',
 'Kev  Mar   Gold\n',
 'Rob  May   Black\n']
>>> [l.split() for l in open('t.tsv', 'r')]
<<<
[['Name', 'Date', 'Color'],
 ['Ray', 'May', 'Gray'],
 ['Alex', 'Apr', 'Green'],
 ['Ann', 'Jun', 'Blue'],
 ['Kev', 'Mar', 'Gold'],
 ['Rob', 'May', 'Black']]
>>> [Entry(*l.split()) for l in open('t.tsv', 'r')]
<<<
[Entry(Name='Name', Date='Date', Color='Color'),
 Entry(Name='Ray', Date='May', Color='Gray'),
 Entry(Name='Alex', Date='Apr', Color='Green'),
 Entry(Name='Ann', Date='Jun', Color='Blue'),
 Entry(Name='Kev', Date='Mar', Color='Gold'),
 Entry(Name='Rob', Date='May', Color='Black')]    >>> {'fooo':e for e in Entry(*l.split()) for l in open('t.tsv', 'r')}
>>> {e.Name:e for e in list(Entry(*l.split()) for l in open('t.tsv', 'r'))}
<<<
{'Alex': Entry(Name='Alex', Date='Apr', Color='Green'),
 'Ann': Entry(Name='Ann', Date='Jun', Color='Blue'),
 'Kev': Entry(Name='Kev', Date='Mar', Color='Gold'),
 'Name': Entry(Name='Name', Date='Date', Color='Color'),
 'Ray': Entry(Name='Ray', Date='May', Color='Gray'),
 'Rob': Entry(Name='Rob', Date='May', Color='Black')}

I think you are thinking on reading the first row as header names. Python has DictReader - https://docs.python.org/2/library/csv.html#csv.DictReader

>>> import csv
>>> for line in csv.DictReader(open('t.tsv')): print line # don't forget to make your file coma-separated. 
{'Date': 'May', 'Color': 'Gray', 'Name': 'Ray'}
{'Date': 'Apr', 'Color': 'Green', 'Name': 'Alex'}
{'Date': 'Jun', 'Color': 'Blue', 'Name': 'Ann'}
{'Date': 'Mar', 'Color': 'Gold', 'Name': 'Kev'}
{'Date': 'May', 'Color': 'Black', 'Name': 'Rob'}

or with dictionary comprehension:

>>> { line['Name']: line for line in csv.DictReader(open('t.tsv')) }
<<<
{'Alex': {'Color': 'Green', 'Date': 'Apr', 'Name': 'Alex'},
 'Ann': {'Color': 'Blue', 'Date': 'Jun', 'Name': 'Ann'},
 'Kev': {'Color': 'Gold', 'Date': 'Mar', 'Name': 'Kev'},
 'Ray': {'Color': 'Gray', 'Date': 'May', 'Name': 'Ray'},
 'Rob': {'Color': 'Black', 'Date': 'May', 'Name': 'Rob'}}
>>> rows_by_name = { line['Name']: line for line in csv.DictReader(open('t.tsv')) }
>>> rows_by_name['Ann']
<<< {'Color': 'Blue', 'Date': 'Jun', 'Name': 'Ann'}

If you want random samples - i suggest first reading a rows into list and then make selection through randbom module. Or... let's do it with Entry:

>>> rows = list(Entry(*l.split()) for l in open('t.tsv', 'r'))
>>> import random
>>> random.sample(rows, 1)
<<< [Entry(Name='Ray', Date='May', Color='Gray')]
>>> random.sample(rows, 1)
<<< [Entry(Name='Alex', Date='Apr', Color='Green')]
>>> random.sample(rows, 1)
<<< [Entry(Name='Name', Date='Date', Color='Color')]
>>> random.sample(rows, 1)
<<< [Entry(Name='Alex', Date='Apr', Color='Green')]
>>> random.sample(rows, 1)
<<< [Entry(Name='Alex', Date='Apr', Color='Green')]
>>> random.sample(rows, 1)
<<< [Entry(Name='Alex', Date='Apr', Color='Green')]
>>> random.sample(rows, 3)
<<<
[Entry(Name='Ray', Date='May', Color='Gray'),
 Entry(Name='Kev', Date='Mar', Color='Gold'),
 Entry(Name='Ann', Date='Jun', Color='Blue')]
>>> random.sample(rows, 3)
<<<
[Entry(Name='Ann', Date='Jun', Color='Blue'),
 Entry(Name='Rob', Date='May', Color='Black'),
 Entry(Name='Name', Date='Date', Color='Color')]
>>> random.sample(rows, 3)
<<<
[Entry(Name='Rob', Date='May', Color='Black'),
 Entry(Name='Ann', Date='Jun', Color='Blue'),
 Entry(Name='Kev', Date='Mar', Color='Gold')]

but beware, that you can load up your memory too much.