CODEWITHSUNDEEP
pythonpython-3.xpandascsvif-statement
Jeremy Lin
Jeremy Lin

Reputation: 258

What is the equivalent of writerow() from csv module in pandas?

I am currently making different functions for a script and I have a function that works perfectly with writerow() however for my other function I used pandas and I am trying to look for the equivalent of that. Im pretty sure to_csv is not what I want.

Here is the same CSV that is being tested on both functions. 

jeffrey,192.168.1.1,example1.com,30220,internet serverice provider 1
mike,192.168.1.2,example2.com,30220,internet service provider 1
frank,192.168.1.3,example3.com,30220,internet service provider 1
lucy,192.168.1.4,example4.com,14619,internet service provider 2
louisa,192.168.1.5,example5.com,14619,internet service provider 2
emily,192.168.1.6,example6.com,3357,internet service provider 3 
john,192.168.1.7,example7.com,210,internet service provider 4

Here is my script that works for writerow()

import csv

document= open("sample.csv")

def start_yes():
    with open ('good_numbers', 'w') as output:
        with document as file:
            output_data = csv.writer(output, delimiter = ',')
            reader = csv.reader(file)
            list_1 = ['3357','210']
            for row in reader:
                if row[3] in list_1:
                    output_data.writerow(row)

Running this script with the sample.csv provides me the results like this, which is what I want.

emily,192.168.1.6,example6.com,3357,internet service provider 3 
john,192.168.1.7,example7.com,210,internet service provider 4

Here is the script that I am trying to find the equivalent of writerow() however using the pandas module.

import pandas as pd 

df = pd.read_csv('sample.csv', header=None)
good_nums = ['3357','210']
bad_nums = ['30220']
maybe_nums = list(set(df[3].tolist()) - set(good_nums + bad_nums))
for asn in df: 
    if asn in df[3]:
    asn.to_csv('output.csv', index=False)

How can I get my result looking like this with the script that uses pandas

lucy,192.168.1.4,example4.com,14619,internet service provider 2
louisa,192.168.1.5,example5.com,14619,internet service provider 2

Any help is greatly appreciated!

Upvotes: 2

Views: 1623

Answers (1)

Corey Levinson
Corey Levinson

Reputation: 1651

You can just use

df = pd.read_csv('sample.csv', header=None)
good_nums = [3357,210]
df.loc[df['numbercolumn'].isin(good_nums)].to_csv('output.csv',index=False)

This is also faster because you don't write it line by line through a loop..

Upvotes: 3

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