Pandas Replace 1st Result in a DataFrame

Let's say I have a dataframe that looks like this:

df4

df4 = pd.DataFrame('Q':['apple', 'apple', 'orange', 'Apple', 'orange'], 'R':['a.txt', 'a.txt', 'a.txt', 'b.txt', 'b.txt'])

>>> df4



Q R
0 apple a.txt
1 apple a.txt
2 orange a.txt
3 Apple b.txt
4 orange b.txt


What I would like to output is this:

Q R
0 breakfast a.txt
1 apple a.txt
2 orange a.txt
3 breakfast b.txt
4 orange b.txt


In other words, case insensitive, I want to search every row in a dataframe, find the first occurrence of certain words (in this case, that word is apple), and replace it with another word.

Is there a way to do this?

2 Answers
2

Here's a vectorised solution with groupby and idxmin:

groupby

idxmin

v = df.Q.str.lower().eq('apple')
v2 = (~v).cumsum().where(v)
df.loc[v2.groupby(v2).idxmin().values, 'Q'] = 'breakfast'

df
Q R
0 breakfast a.txt
1 apple a.txt
2 orange a.txt
3 breakfast b.txt
4 orange b.txt


I just really wanted to answer this question.

def swap_first(s):
swap = 1
luk4 = 'apple'
for x in s:
if x.lower() in luk4 and swap:
yield 'breakfast'
swap ^= 1
else:
yield x
if x not in luk4:
swap ^= 1

df4.assign(Q=[*swap_first(df4.Q)])

Q R
0 breakfast a.txt
1 apple a.txt
2 orange a.txt
3 breakfast b.txt
4 orange b.txt


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