Searching a list of strings within a column of data

Question

I have a column of data that looks like this:

import pandas as pd
import numpy as np

   Items
0  Product A + Product B + Product C   
1  Product A + Product B + Product B1 + Product C1 
2

I would like to look through the items and find out if the column contains a few specific items, relating to products I am interested in flagging as containing within the items column :

My_Items = ['Product B', 'Product C', 'Product C1']

I've tried the following lambda function but it is not picking up the strings i'm searching if there is more than 1 product within the column:

df['My Items'] = df['Items'].apply(lambda x: 'Contains my items' if x in My_Items else '')

Does anyone know how can search for multiple strings in a list within a lambda function?

Thank you for any help or suggestions.

Kind regards

What is expected output?

jezrael
– jezrael

2020-04-24 10:22:43 +00:00
Commented Apr 24, 2020 at 10:22 — jezrael
– jezrael, Commented Apr 24, 2020 at 10:22

jezrael · Accepted Answer · 2020-04-24 10:30:42Z

3

Use Series.str.count for count matched values and then tested with Series.gt for greater like 1:

mask = df.Items.str.count('|'.join(My_Items)).gt(1)

df['My Items'] = np.where(mask,'Contains 2 or more items', '')
print (df)
                                             Items                  My Items
0                Product A + Product B + Product C  Contains 2 or more items
1  Product A + Product B + Product B1 + Product C1  Contains 2 or more items

Details:

print (df.Items.str.count('|'.join(My_Items)))
0    2
1    3
Name: Items, dtype: int64

edited Apr 24, 2020 at 10:30

answered Apr 24, 2020 at 10:16

jezrael

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Comments

yatu · Accepted Answer · 2020-04-24 10:29:27Z

IIUC you may use str.findall and check we get at least 2 matches:

import numpy as np

m = df.Items.str.findall('|'.join(My_Items)).str.len().ge(2)
df['My items'] = np.where(m, 'Contains at least 2 items', '')

If we check with an additional row containing only 1 of the products:

print(df)

                        Items  \
0                Product A + Product B + Product C      
1  Product A + Product B + Product B1 + Product C1     
2                            Product A + Product D    

                    My items  
0  Contains at least 2 items  
1  Contains at least 2 items  
2

Where df.Items.str.findall('|'.join(My_Items)) is giving you a list with all found matches:

df.Items.str.findall('|'.join(My_Items))

 [Product B, Product C]
1    [Product B, Product B, Product C]
2                                   []
Name: Items, dtype: object

Amen_90 · Accepted Answer · 2020-04-24 13:41:14Z

-1

Thank you guys! The solution I was looking for ended up being a combination of both of your answers!

What I ended up doing was this for the mask, so I could filter:

DF['My_Items'] = DF.Items.str.findall('|'.join(My_list)).str.len().gt(1)

Then this for the list of items, so I can now analyse the combinations:

DF['My_Items'] = DF.Items.str.findall('|'.join(My_list)).astype(str)

answered Apr 24, 2020 at 13:41

Amen_90

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