How can I replace the data 'Beer','Alcohol','Beverage','Drink' with only 'Drink'.
df.replace(['Beer','Alcohol','Beverage','Drink'],'Drink')
doesn't work
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3If your question was answered, please reward the efforts of those who helped you. Accept the most helpful answer. You can also upvote all other useful answers. Please make it a habit, it helps the community.cs95– cs952017-10-26 16:58:54 +00:00Commented Oct 26, 2017 at 16:58
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This code does work in pandas now, see example 3 on pandas.pydata.org/pandas-docs/stable/reference/api/…00schneider– 00schneider2020-04-23 08:58:38 +00:00Commented Apr 23, 2020 at 8:58
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6 Answers
You almost had it. You need to pass a dictionary to df.replace.
df
Col1
0 Beer
1 Alcohol
2 Beverage
3 Drink
df.replace(dict.fromkeys(['Beer','Alcohol','Beverage','Drink'], 'Drink'))
Col1
0 Drink
1 Drink
2 Drink
3 Drink
This works for exact matches and replacements. For partial matches and substring matching, use
df.replace(
dict.fromkeys(['Beer','Alcohol','Beverage','Drink'], 'Drink'),
regex=True
)
This is not an in-place operation so don't forget to assign the result back.
3 Comments
piRSquared
Ha! I was going to
df.replace({k: 'Drink' for k in ['Beer','Alcohol','Beverage','Drink']}) But instead, I learned about dict.fromkeys
2Toad
Won't passing
inplace=True to df.replace make it an in-place operations, if desired?
cs95
@2Toad it would but I don't recommend it: stackoverflow.com/a/60020384/4909087
Try the following approach:
lst = ['Beer','Alcohol','Beverage','Drink']
pat = r"\b(?:{})\b".format('|'.join(lst))
df = df.replace(pat, 'Drink', regexp=True)
answered Oct 24, 2017 at 21:40
MaxU - stand with Ukraine
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1 Comment
BENY
Nice one , just do not know why yours and mine are different but can get the same result ...Sorry I am not quit work with strings...can you refer some link for future studying
Looks like different from MaxU's solution :)
df.replace({'|'.join(['Beer','Alcohol','Beverage','Drink']):'Drink'},regex=True)
1 Comment
Chang Zhao
which python version is it ?
It seems that your initial method of doing it works in the the latest iteration of Python.
df.replace(['Beer','Alcohol','Beverage','Drink'],'Drink', inplace=True)
Should work
Comments
Slight change in earlier answers: Following code Replacing values of specific column/Columns
df[['Col1']] = df[['Col1']].replace(dict.fromkeys(['Beer','Alcohol','Beverage','Drink'], 'Drink'))
Comments
Not relevant to your exact case using strings, but relevant to the question as stated in the title:
If you have a range of numbers you would like to replace you can provide range() as a dict key.
# Dymmy dataframe with two columns
df = pd.DataFrame(dict(a=[1, 2, 3, 4, 5], b=[66, 44, 33, 22, 77]))
# Mapping that will replace 1 with 'x', 2, 3, 4 with 'y' and 5 with 'z' in column 'a'
mapping = {"a": {1: "x", range(2, 5): "y", 5: "z"}}
df.replace(mapping)
