Matching two data different columns from two different dataframes

Question

So I have two different Dataframes, both dataframes have columns known as "Domains" and show domains from different sources. The domains are clean and look like www.google.com, www.facebook.com, and not like www.facebook.com/4938249084.

The goal I am aiming to achieve is to know if any of the domains in DF1 is in the domains of DF2 and if is the in DF2, Append DF1 domain to the list. Here is the code I have written up.

Just so you guys have an Idea, DF1 has ~4,000 records v DF2 has ~7,000 records.

DF1

                 Domains
0                              NaN
1    www.hawaiiantimeathletics.com
2                              NaN
3              www.beach-elite.com
4                              NaN
5           www.dreamingoldvbc.com
6           www.pacificunionvb.com
7           www.alabamajuniors.com
8     www.birminghamvolleyball.com
9         www.magiccitythunder.com

DF2

                 Domains
0            www.labcsandiego.com
1         www.ahavavolleyball.com
2        www.northernelite-va.com
3               www.theedgevc.com
4                  divadallas.org
5            www.beach-elite.com
6         650xtremevolleyball.org
7             www.clubsouthvb.com
8    www.northidahovolleyball.com
9        wajvolleyball.site123.me

In this Example, The only domain that should be appended into the list is 'www.beach-elite.com'.

Here's the code I wrote

def match_domain(col1,col2):
    list1 = []
    for a in col1:
        v1 = a
    for b in col2:
        v2 = b 
        if v1 == v2:
            list1.append(v1)
            print(v1)
        elif v1 != v2:
            print('none')

match_domain(DF1, DF2)

Thank you in Advance !

MYousefi · Accepted Answer · 2022-02-15 04:46:54Z

1

You can use the isin function to determine this.

import pandas as pd
df1 = pd.DataFrame({'Domains': ['NaN', 'www.hawaiiantimeathletics.com', 'NaN', 'www.beach-elite.com', 'www.dreamingoldvbc.com', 'www.pacificunionvb.com', 'www.alabamajuniors.com', 'www.birminghamvolleyball.com', 'www.magiccitythunder.com']})
df2 = pd.DataFrame({'Domains': ['www.labcsandiego.com', 'www.ahavavolleyball.com', 'www.northernelite-va.com', 'www.theedgevc.com', 'divadallas.org', 'www.beach-elite.com', '650xtremevolleyball.org', 'www.clubsouthvb.com', 'www.northidahovolleyball.com', 'wajvolleyball.site123.me']})

df1.Domains[df1.Domains.isin(df2.Domains)].unique()

This should give you the intersection of the domains columns.

edited Feb 15, 2022 at 4:46

answered Feb 15, 2022 at 4:33

MYousefi

1,0181 gold badge6 silver badges10 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

Umar Yusuf · Accepted Answer · 2022-02-15 05:07:59Z

0

This can be solved using list comprehension. Convert the two data frames to lists and lookup on list in the other as follow:-

df1:

Domains
NaN
www.hawaiiantimeathletics.com
NaN
www.beach-elite.com
NaN
www.dreamingoldvbc.com
www.pacificunionvb.com
www.alabamajuniors.com
www.birminghamvolleyball.com
www.magiccitythunder.com

df2:

Domains
www.labcsandiego.com
www.ahavavolleyball.com
www.northernelite-va.com
www.theedgevc.com
divadallas.org
www.beach-elite.com
650xtremevolleyball.org
www.clubsouthvb.com
www.northidahovolleyball.com
wajvolleyball.site123.me

Code:

list1 = [ domain for domain in df1['Domains'].tolist() if domain in df2['Domains'].tolist() ]

answered Feb 15, 2022 at 5:07

Umar Yusuf

9922 gold badges14 silver badges30 bronze badges

Collectives™ on Stack Overflow

Matching two data different columns from two different dataframes

2 Answers 2

Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related