Regroup pandas column into 2D list based on another column

Question

I have a pandas dataset with a column of words and a column of integer (0,1). All words that appear between a zero (first integer, or after a 1) and a 1(including) should be put into a 2D array.

Let me explain:

Consider this pandas dataframe:

import pandas as pd

df = pd.DataFrame(columns=['Text','Selection_Values'])
df["Text"] = ["Hi", "this is", "just", "a", "single", "sentence.", "This", "is another one."]
df["Selection_Values"] = [0,0,0,0,0,1,0,1]
print(df)

This is the example dataset:

              Text  Selection_Values
0               Hi                 0
1          this is                 0
2             just                 0
3                a                 0
4           single                 0
5        sentence.                 1
6             This                 0
7  is another one.                 1

The expected result should be:

[["Hi this is just a single sentence."],["This is another one"]]

Do you have any idea of how to go about this ?

This is what I have done so far:

result = []

s = ""
for i in range(len(df["Text"])):
    s += df["Text"][i] + " "
    if df["Selection_Values"][i] == 1:
        result.append([s])
        s = ""

It works:

[['Hi this is just a single sentence. '], ['This is another one. ']]

...but it might not be the best method. It does not make use of the pandas framework at all.

Answer 1

Using shift + ' '.join. This assumes of course that every sentence has a closing 1 and there are no hanging sentences.

---

g = df['Selection_Values'].shift().eq(1).cumsum()

df['Text'].groupby(g).agg(' '.join).tolist()

['Hi this is just a single sentence.', 'This is another one.']