How to extract value from an array based on condition in pandas or numpy?

Question

I have dataframe with the following values

        Bird    Color
   0    Parrot  ['Light_Blue','Green','Dark_Blue']
   1    Eagle   ['Sky_Blue','Black','White', 'Yellow','Gray']
   2    Seagull ['White','Jet_Blue','Pink', 'Tan','Brown', 'Purple']

I want to create a column called 'No Blue', where it will only list array elements without the word "Blue" in it.

Like this:

    Bird    Color                                                No Blue
0   Parrot  ['Light_Blue','Green','Dark_Blue']                   ['Green']
1   Eagle   ['Sky_Blue','Black','White', 'Yellow','Gray']        ['Black', 'White', 'Yellow', 'Gray']
2   Seagull ['White','Jet_Blue','Pink', 'Tan','Brown', 'Purple'] ['White', 'Pink', 'Tan', 'Brown', 'Purple']

This is the closest thing I have to a solution

>>> Eagle = ['Sky_Blue','Black','White', 'Yellow','Gray']
>>> matching = [x for x in Eagle if "Blue" not in x]
>>> matching
['Black', 'White', 'Yellow', 'Gray']

I'm wondering how to do it using str.extract or str.replace etc — Hryhorii Pavlenko
– Hryhorii Pavlenko, Commented Aug 15, 2019 at 12:36
Since you are iterating over a list within in each row, I think passing .apply(lambda...) is more efficient — Celius Stingher
– Celius Stingher, Commented Aug 15, 2019 at 12:54

ivallesp · Accepted Answer · 2019-08-15 12:17:11Z

1

I would use this code:

df["noBlue"]=df.Color.apply(lambda x: [v for v in x if "Blue" not in v])

answered Aug 15, 2019 at 12:17

ivallesp

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Celius Stingher · Accepted Answer · 2019-08-15 12:21:37Z

I'm running this from command, so bare my prints!:

import pandas as pd
a = {'Bird':['Parrot','Eagle','Seagull'],'Color':[['Light_Blue','Green','Dark_Blue'],['Sky_Blue','Black','White', 'Yellow','Gray'],['White','Jet_Blue','Pink', 'Tan','Brown', 'Purple']]}
df = pd.DataFrame(a)
print(df)

Here I'm matching your results:

      Bird                                        Color
0   Parrot               [Light_Blue, Green, Dark_Blue]
1    Eagle       [Sky_Blue, Black, White, Yellow, Gray]
2  Seagull  [White, Jet_Blue, Pink, Tan, Brown, Purple]

This will create your new column based on a condition:

df["Not_Blue"] = df['Color'].apply(lambda x: [a for a in x if "Blue" not in a])
print(df)

Output:

      Bird                                        Color                           Color_Not_Blue
0   Parrot               [Light_Blue, Green, Dark_Blue]                            [Green]
1    Eagle       [Sky_Blue, Black, White, Yellow, Gray]       [Black, White, Yellow, Gray]
2  Seagull  [White, Jet_Blue, Pink, Tan, Brown, Purple]  [White, Pink, Tan, Brown, Purple]

Karn Kumar · Accepted Answer · 2019-08-15 15:57:23Z

0

Try with this:

>>> df['color'].str.replace(r'\w+_Blue\b', "")
0                                 ['','Green','']
1           ['','Black','White', 'Yellow','Gray']
2    ['White','','Pink', 'Tan','Brown', 'Purple']

For personal curiosity, I have opened another SO thread to get it with replace and got below solution if you are using pandas version 0.25 .

See the thread for another solutions..

 df['color'].str.replace(r'\w+_Blue\b', '').explode().loc[lambda x : x!=''].groupby(level=0).apply(list)

edited Aug 15, 2019 at 15:57

answered Aug 15, 2019 at 13:40

Karn Kumar

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