Python - Transpose Columns To Rows Within Data Operation And Before Writing To File

I have developed a public and open source App for Splunk (Nmon performance monitor for Unix and Linux Systems, see https://apps.splunk.com/app/1753/) A master piece of the App is a

Solution 1:

The goal is to transpose the data such as we will have in the header "time,device,value"

This rough transposition logic looks like this:

text = '''time,sda,sda1,sda2,sda3,sda5,sda6,sda7,sdb,sdb1,sdc,sdc1,sdc2,sdc3
26-JUL-2014 11:10:44,4.4,0.0,0.0,0.0,0.4,1.9,2.5,0.0,0.0,10.2,10.2,0.0,0.0
26-JUL-2014 11:10:54,4.8,0.0,0.0,0.0,0.3,2.0,2.6,0.0,0.0,5.4,5.4,0.0,0.0
26-JUL-2014 11:11:04,4.8,0.0,0.0,0.0,0.4,2.3,2.1,0.0,0.0,17.8,17.8,0.0,0.0
26-JUL-2014 11:11:14,2.1,0.0,0.0,0.0,0.2,0.5,1.5,0.0,0.0,28.2,28.2,0.0,0.0
'''import csv

for d in csv.DictReader(text.splitlines()):
    time = d.pop('time')
    for device, value insorted(d.items()):
        print time, device, value

Putting it all together into a complete script looks something like this:

import csv

withopen('transposed.csv', 'wb') as destfile:
    writer = csv.writer(destfile)
    writer.writerow(['time', 'device', 'value'])
    withopen('data.csv', 'rb') as sourefile:
        for d in csv.DictReader(sourcefile):
            time = d.pop('time')
            for device, value insorted(d.items()):
                row = [time, device, value]
                writer.writerow(row)