Merge Two Tables (csv) If (table1 Column A == Table2 Column A)

I have two CSV's, openable in Numbers or Excel, structured: | word | num1 | and | word | num2 | if the two words are equal (like they're both 'hi' and 'hi') I want it to become: |

Solution 1:

For csv, I always reach for the data analysis library pandas. http://pandas.pydata.org/

import pandas as pd

df1 = pd.read_csv('file1.csv', names=['word','num1'])
df2 = pd.read_csv('file2.csv', names=['word','num2'])
df3 = pd.merge(df1, df2, on='word')
df3.to_csv('merged_data.csv')

Solution 2:

Use a dict:

withopen('file1.csv', 'rb') as file_a, open('file2.csv', 'rb') as file_b:
    data_a = csv.reader(file_a)
    data_b = dict(csv.reader(file_b))  # <-- dictwithopen('out.csv', 'wb') as file_out:
        csv_out = csv.writer(file_out)
        for word, num_a in data_a:
            csv_out.writerow([word, num_a, data_b.get(word, '')])  # <-- edit

(untested)

Solution 3:

I think what you're looking for is zip, to let you iterate the two CSVs in lock-step:

withopen('file1.csv', 'rb') as f1, open('file2.csv', 'rb') as f2:
    r1, r2 = csv.reader(f1), csv.reader(f2)
    withopen('out.csv', 'wb') as fout:
        w = csv.writer(fout)
        for row1, row2 inzip(r1, r2):
            if row1[0] == row2[0]:
                w.writerow([row1[0], row1[1], row2[1]])

I'm not sure what you wanted to happen if they're not equal. Maybe insert both rows, like this?

            else:
                w.writerow([row1[0], row1[1], ''])
                w.writerow([row2[0], '', row2[1]])