CSV选择多个列

Question

I have this CSV file whereby it contain lots of information. I have coded a program which are able to count what are inside the columns of 'Feedback' and the frequency of it.

My problem now is that, after I have produced the items inside 'Feedback' columns, I want to specifically bring out another columns which tally to the 'Feedback' columns.

Some example of the CSV file is as follow:

Feedback      Description    Status
Others        Fire Proct     Complete
Complaints    Grass          Complete
Compliment    Wall           Complete
...           ...            ...

With the frequency of the 'Feedback' columns, I now want to show, let's say if I select 'Complaints'. Then I want everything that tally with 'Complaints' from Description to show up.

Something like this:

Complaints    Grass
Complaints    Table
Complaints    Door
...           ...

Following is the code I have so far:

import csv, sys, os, shutil
from collections import Counter

reader = csv.DictReader(open('data.csv'))
result = {}
for row in reader:
    for column, value in row.iteritems():
        result.setdefault(column,[]).append(value)

list = []
for items in result['Feedback']:
    if items == '':
        items = items
    else:
        newitem = items.upper()
        list.append(newitem)

unique = Counter(list)

for k, v in sorted(unique.items()):
    print k.ljust(30),' : ', v

This is only the part whereby it count what's inside the 'Feedback' Columns and the frequency of it.

Answer 1

You could also store a defaultdict() holding a list of entries for each category as follows:

import csv
from collections import Counter, defaultdict

with open('data.csv', 'rb') as f_csv:
    csv_reader = csv.DictReader(f_csv)

    result = {}
    feedback = defaultdict(list)

    for row in csv_reader:
        for column, value in row.iteritems():
            result.setdefault(column, []).append(value)
        feedback[row['Feedback'].upper()].append(row['Description'])

data = []

for items in result['Feedback']:
    if items == '':
        items = items
    else:
        newitem = items.upper()
        data.append(newitem)

unique = Counter(data)

for k, v in sorted(unique.items()):
    print "{:20} : {:5}  {}".format(k, v, ', '.join(feedback[k]))

This would display your output as:

COMPLAINTS           :     2  Grass, Door
COMPLIMENT           :     2  Wall, Table
OTHERS1              :     1  Fire Proct

Or on multiple lines if instead you used:

    print "{:20} : {:5}".format(k, v)
    print '  ' + '\n  '.join(feedback[k])

When using the csv library, you should open your file with rb in Python 2.x. Also avoid using list as a variable name as this overwrites the Python list() function.

Note: It is easier to use format() when printing aligned data.

Answer 2

You can do it with the code at the very end of this snippet, which is derived from the code in your question. I modified how the file is read by using a with statement which insures that it is closed when it's no longer needed. I also changed the name of the variable named list you had. because it hides the name of the built-in type and is considered by most to be a poor programming practice. See PEP 8 - Style Guide for Python Code for more on this and related topics.

For testing purposes, I also added a couple more rows of 'Complaints' type of 'Feedback' items.

import csv
from collections import Counter

with open('information.csv') as csvfile:
    result = {}
    for row in csv.DictReader(csvfile):
        for column, value in row.iteritems():
            result.setdefault(column, []).append(value)

items = [item.upper() for item in result['Feedback']]
unique = Counter(items)

for k, v in sorted(unique.items()):
    print k.ljust(30), ' : ', v

print
for i, feedback in enumerate(result['Feedback']):
    if feedback == 'Complaints':
        print feedback, '  ', result['Description'][i]

Output:

COMPLAINTS                      :  3
COMPLIMENT                      :  1
OTHERS                          :  1

Complaints    Grass
Complaints    Table
Complaints    Door