Compare two column in python and return matches in first table

Question

Help to compare two columns in different tables by cycle and return the matches to the first table.

data1:
|name   | revenue |
|-------|---------|
|Alice  | 700     |
|Bob    | 1000    |
|Gerry  | 300     |
|Alex   | 600     |
|Kyle   | 800     |

data2:
|Name   | revenue |
|-------|---------|
|Bob    | 900     |
|Gerry  | 400     |

result data1:
|name   | revenue  |  name_result |
|-------|----------|--------------|
|Alice  | 700      |              |
|Bob    | 1000     |  Bob         |
|Gerry  | 300      |  Gerry       |
|Alex   | 600      |              |
|Kyle   | 800      |              |

I tried using this code, but got all empty values:

import pandas as pd
import numpy as np

def group_category(category):
    for name in data['name']: 
        if name in data2['Name']:
            return name
        else: name = ''
        return name 
data['name_result'] = data['name'].apply(group_category)

which module are you using for manupulating dataframes? `pandas` or `r`? — Anurag Dabas, Jul 09 '21 at 12:15
have you read [pandas-merging-101](https://stackoverflow.com/questions/53645882/pandas-merging-101)? — Anurag Dabas, Jul 09 '21 at 12:57
How to do it without merge? Later I want use a same code in another task: def group_category(category): for name in data['name']: if name in data2['Name']: return 'organic' else: name return name data['name_result'] = data[data['name'] == 'notorganic'].apply(group_category) — Alex, Jul 09 '21 at 13:36
btw If your query is solved then you can try considering accepting the answer(click on the tick to make it green)...Thnx ***:)*** — Anurag Dabas, Jul 09 '21 at 14:53

score 0 · Answer 1 · answered Jul 09 '21 at 13:54

0

use:

def group_category(category):
    if category in df2['Name'].unique():
            return category
    else:
        return ''

#Finally:
#Since you are going to use this function on Series so used map() in place of apply()
df1['name_result']=df1['name'].map(group_category)

OR

via isin() and where():

df1['name_result']=df1['name'].where(df1['name'].isin(df2['Name']),'')

answered Jul 09 '21 at 13:54

Anurag Dabas

23,866
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How can I overwrite a cell if the conditions are the same and leave the old value if everything else? – Alex Jul 12 '21 at 12:31

score 0 · Answer 2 · answered Aug 05 '21 at 02:54

0

I found solution:

df1.loc[df1['name'].isin(df2['name_result'].unique()), 'brand'] = 'Adidas Collection'

answered Aug 05 '21 at 02:54

Alex

1
2

Compare two column in python and return matches in first table

2 Answers2