比较数据框中的两个熊猫系列并对其应用说明

Question

I have been trying to compare substrings of two series from a pandas dataframe. The two series are "titles" and "News" which are respectively the news headline and news body from a newspaper website that I scraped from. Now, many of the "News" indexes have the headline included in it at the first line and I want to remove that from the "News" series.

For example:

df["News"][0] = "Mother Killed, police official injured in Madaripur road accidentA woman was killed .... flee the scene.AH/MUS"
df["titles"][0] = "Mother Killed, police official injured in Madaripur road accident"

I want to remove the titles from the News. In the above example, this should yield "A woman was killed .... flee the scene.AH/MUS"

I have done it like this:

df["replaced"] = [(df["News"][i].replace(df["titles"][i], ""))
                   for i in range(df.shape[0])
                 ]

This does the work, but I want to know what should be the fastest method for this. To be specific, I am looking for a more pandas way and don't want to loop over/use list comprehension. What could be a way of doing this so that I can apply it to the whole series without looping over?

Answer 1

Try that it will work like charm

def getit(row):
 try:
  return row.get("News").replace(row.get("titles"),"")
 except:
  return row.get("News") # in case row.get("titles") return non-string

df["replaced"] = df.apply(getit , axis = 1)