Python: Replace One Word In A Sentence With A List Of Words And Put Thenew Sentences In Another Column In Pandas

I have a dataframe in which SOME sentences contain the word 'o'clock' and I want to replace the time mentioned before it with the list of hours I have and put the new sentences in

Solution 1:

Use:

# STEP 1
df1 = data['sentences'].str.extract(
    r"(?i)(?P<before>.*)\s(?P<clock>\w+(?=\so'clock))\s(?P<after>.*)")

# STEP 2
df1['clock'] = df1['clock'].str.replace(
    r'\w+', ','.join(my_list)).str.split(',')

# STEP 3
data['new_sentences'] = df1.dropna().explode('clock').agg(
    ' '.join, 1).groupby(level=0).agg(', '.join)

# STEP 4
data['new_sentences'] = data['new_sentences'].fillna(data['sentences'])

Explanation/Steps:

STEP 1: Use Series.str.extract along with the given regex pattern to create a three column dataframe where the first col corresponds to the sentence before the clock e.g. 10, the middle column corresponds to clock itself and right column corresponds to the sentence after the clock.

# df1
                  before  clock    after
0      I have a class at    ten  o'clock
1                    NaN    NaN      NaN
2  she goes to school at  eight  o'clock

STEP 2: Use Series.str.replace to replace the tokens in the clock column with all the items in my_list. Then use Series.str.split to split the replaced tokens around the delimiter ,.

# df1
                  before                    clock    after
0      I have a class at  [two, three, five, ten]  o'clock
1                    NaN                      NaN      NaN
2  she goes to school at  [two, three, five, ten]  o'clock

STEP 3: Dataframe.explode to explode the dataframe df1 around column clock the use the .agg to join the columns along axis 1. Then use groupby on level 0 to agg this datframe further.

# data
                             sentences                                      new_sentences
0        I have a class at ten o'clock  I have a class at two o'clock, I have a class ...
1                     she is my friend                                                NaN
2  she goes to school at eight o'clock  she goes to school at two o'clock, she goes to...

STEP 4: Finally use Series.fillna to fill the missing values in the new_sentences column from the corresponding sentences column.

# data
                             sentences                                      new_sentences
0        I have a class at ten o'clock  I have a class at two o'clock, I have a class ...
1                     she is my friend                                   she is my friend
2  she goes to school at eight o'clock  she goes to school at two o'clock, she goes to...

Solution 2:

Is this in line with what you were expecting?

import re
data= {"sentences":["I have a class at ten o'clock", "she is my friend", "she goes to school at eight o'clock"]}
my_list=['two', 'three','five','ten']

regex = re.compile(r"(\w+) (?=o'clock)", re.IGNORECASE)
new = []

for i in data["sentences"]:
    for j in my_list:
        new.append(re.sub(regex, j + ' ', i))

new = list(set(new))

print(new)

Output:

I have a class at two o'clock
I have a class at ten o'clock
she goes to school at two o'clock
she goes to school at five o'clock
I have a class at five o'clock
I have a class at three o'clock
she goes to school at ten o'clock
she goes to school at three o'clock
she is my friend

OR equivalent:

import re
data= {"sentences":["I have a class at ten o'clock", "she is my friend", "she goes to school at eight o'clock"]}
my_list=['two', 'three','five','ten']
regex = re.compile(r"(\w+) (?=o'clock)", re.IGNORECASE)
x = list(set([re.sub(regex, j + ' ', i) for j in my_list for i in data["sentences"]]))