Group data from a CSV file by field value

Question

I have a csv file which has duplicate value in first column . I want to collect all value of second column in a list for one value of first column

column1 column2
a        54.2
s        78.5
k        89.62
a        77.2
a        65.56

I want to get like

print a  # [54.2,77.2,65.56]
print s  # [78.5]
print k  # [89.62]

Answer 1

It seems fairly straightforward using python's CSV reader.

data.csv

a,54.2
s,78.5
k,89.62
a,77.2
a,65.56

script.py

import csv

result = {}

with open('data.csv', 'rb') as csvfile:
    csvreader = csv.reader(csvfile, delimiter=',', quotechar='"')
    for row in csvreader:
        if row[0] in result:
            result[row[0]].append(row[1])
        else:
            result[row[0]] = [row[1]]

print result

output

{
    'a': ['54.2', '77.2', '65.56'], 
    's': ['78.5'], 
    'k': ['89.62']
}

---

As @Pete poined out, you can beautify it using defaultdict:

script.py

import csv
from collections import defaultdict

result = defaultdict(list)  # each entry of the dict is, by default, an empty list

with open('data.csv', 'rb') as csvfile:
    csvreader = csv.reader(csvfile, delimiter=',', quotechar='"')
    for row in csvreader:
        result[row[0]].append(row[1])

print result

Answer 2

One way of doing this is by using pandas, populate a dataframe, use groupby and then apply list to all the groups:

import pandas as pd

df = pd.DataFrame({'column1':['a','s','k','a','a'],'column2': 
[54.2,78.5,89.62,77.2,65.56]})
print(df.groupby('column1')['column2'].apply(list))

output:

column1
a    [54.2, 77.2, 65.56]
k                [89.62]
s                 [78.5]
Name: column2, dtype: object