Splitting based on condtions

Question

Say I have df as follows:

MyCol
Red Motor
Green Taxi 
Light blue small Taxi  
Light blue big Taxi 

I would like to split the color and the vehicle into two columns. I used this command to split the last word. But sometimes, there is a 'big' or 'small' associated with the car name. How can do the splitting with conditions?

df[['color','vehicle']] = df.myCol.str.rsplit(pat=' ', n=1, expand=True)

Answer 1

I think the best approach is to use extract with a regex pattern

df['MyCol'].str.extract('^(.*?)\s((?:small|big)?\s?\w+)$')

---

            0           1
0         Red       Motor
1       Green        Taxi
2  Light blue  small Taxi
3  Light blue    big Taxi

Regex details:

• ^: Matches start of the string
• (.*?): first capturing group
  • .*?: matches any character zero or more times but as few times as possible (lazy match)
• \s: Matches the space
• ((?:small|big)?\s?\w+): Second capturing group
  • (?:small|big)? : matches small or big zero or one time
  • \s?: matches space zero or one time
  • \w+: matches word characters oner or more times
• $: matches end of the string

The Series.str.extract is used here to extracts two groups using a regular expression. The first group is before a whitespace and the second group is after the whitespace. The second group may contain the word "small" or "big" and returns a new DataFrame with two columns containing the extracted groups.