Accessing columns in a csv using python

Question

I am trying to access data from a CSV using python. I am able to access entire columns for data values; however, I want to also access rows, an use like and indexed coordinate system (0,1) being column 0, row 1. So far I have this:

#Lukas Robin 
#25.07.2021
import csv
with open("sun_data.csv") as sun_data:
        sunData = csv.reader(sun_data, delimiter=',')
        global data
        for data in sunData:
            print(data)

I don't normally use data tables or CSV, so this is a new area for me.

You perhaps consider switching to e.g. pandas, which has convenient methods for reading in a CSV-file as a dataframe; pandas.pydata.org/pandas-docs/version/0.23/generated/… — Mikael Öhman
– Mikael Öhman, Commented Jul 25, 2021 at 14:25

AirSquid · Accepted Answer · 2021-07-25 14:59:12Z

1

As mentioned in the comment, you could make the jump to using pandas and spend a little time learning that. It would be a good investment of time if you plan to do much data analysis or work with data tables regularly.

If you just want to pull in a table of numbers and access it as you request, you are perfectly fine using csv package and doing that. Below is an example...

If your .csv file has a header in it, you can simply add in next(sun_data) before starting the inner loop to advance the iterator and let that data fall on the floor...

import csv
f_in = 'data_table.csv'
data = []  # a container to hold the results
with open(f_in, 'r') as source:
    sun_data = csv.reader(source, delimiter=',')
    for row in sun_data:
        # convert the read-in values to float data types (or ints or ...)
        row = [float(t) for t in row]
        # append it to the data table
        data.append(row)

print(data[1][0])

answered Jul 25, 2021 at 14:59

AirSquid

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2 Comments

empty-engineer Over a year ago

Thank you, im gonna take the time to learn panda and then ill compare the runtime and use the fastest one

AirSquid Over a year ago

Sure. Your data table would have to be quite huge to have it make an appreciable difference in speed, I think.

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