How to update value within a column?

Question

I would need to change label if at least one of data frame's columns contain one of the following words:

check_words=['pit','stop','PIT','STOP','Pit','Stop']

A sample of rows in my dataframe is:

import pandas as pd
import numpy as np
df = pd.DataFrame(np.array([['Ferrari was hit by a radio communication blackout' , 'Scuderia Ferrari trying a double pit stop', ' If Ferrari takes nothing else away from the 2019 season, it must learn from its mistakes across the season'], ['We may use the following original news sources for stories', 'Sebastian Vettel insisted he trusts in Ferrari', 'During the recent Grand Prix of Italy, the Scuderia Ferrari team managed to execute one of the fastest pit stops ever performed during a Formula 1 race']]),
                   columns=['Text1', 'Short','Data'])

I created a column Label as follows:

df['Label']='No Pit' to identify if a column contains or does not contain the words in the list above. If it contains a word within that list, then I would need to change label in 'Pit'.

Could you please tell me how I can change it?

What will be expected output for the above given input ? – sushanth Jul 05 '20 at 03:38 — sushanth, Jul 05 '20 at 03:38

score 0 · Answer 1 · answered Jul 05 '20 at 03:46

you can do this by make a dataframe of list andd then add it to your main dataframe here is code.

import pandas as pd
import numpy as np

check_words=['pit','stop','PIT','STOP','Pit','Stop']

df = pd.DataFrame(np.array([['Ferrari was hit by a radio communication blackout' , 'Scuderia Ferrari trying a double pit stop', ' If Ferrari takes nothing else away from the 2019 season, it must learn from its mistakes across the season'], ['We may use the following original news sources for stories', 'Sebastian Vettel insisted he trusts in Ferrari', 'During the recent Grand Prix of Italy, the Scuderia Ferrari team managed to execute one of the fastest pit stops ever performed during a Formula 1 race']]),columns=['Text1', 'Short','Data'])

df['Label'] = pd.DataFrame(check_words)

print(df)

Output

0   Ferrari was hit by a radio communication blackout   Scuderia Ferrari trying a double pit stop   If Ferrari takes nothing else away from the 2...    pit
1   We may use the following original news sources...   Sebastian Vettel insisted he trusts in Ferrari  During the recent Grand Prix of Italy, the Scu...   stop

This does not answer the OP's question, review the answer before posting. — sushanth, Jul 05 '20 at 03:51
you should check this https://stackoverflow.com/questions/3271478/check-list-of-words-in-another-string Upvote please. — Jeel Gondaliya, Jul 05 '20 at 04:32

score 0 · Accepted Answer · answered Jul 05 '20 at 05:11

0

Try this:

l = pd.DataFrame(np.vectorize(lambda r: any(x in r for x in check_words))(df.iloc[:3].values))
df['Label'] = l.any(1).agg(lambda x: 'pit' if x else 'not pit')

Hope this helps !!!

answered Jul 05 '20 at 05:11

luckyCasualGuy

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using custom function with for loop is slower than using inbuilt functions... This approach cuts execution time by 50% – luckyCasualGuy Jul 05 '20 at 10:11

score 0 · Answer 3 · answered Jul 05 '20 at 07:48

I use my own function (chk_word) to check and write 'check_words'.

def chk_word(row):
    for c in check_words:
        if row.str.contains(c).any():
            return c
df['Label'] = df.apply(chk_word, axis=1)
df
Text1   Short   Data    Label
0   Ferrari was hit by a radio communication blackout   Scuderia Ferrari trying a double pit stop   If Ferrari takes nothing else away from the 2...    pit
1   We may use the following original news sources...   Sebastian Vettel insisted he trusts in Ferrari  During the recent Grand Prix of Italy, the Scu...   pit

How to update value within a column?

3 Answers3