How to explode Python Pandas Dataframe based on string and criteria

How to turn StringDataFrame:

Into this:

Based on this ThingsDataFrame

option 1

You can use merge/map.

# you could skip this mapping if you used "Jon likes {animal}."
mapper = {'ExplodeAnimals': 'animal', 'ExplodeFruit': 'fruit'}

out = (StringDataFrame['String']
  .str.extract(r'(?P<String>.*) {(?P<Type>.*)}')
  .assign(Type=lambda d: d['Type'].map(mapper))
  .merge(ThingsDataFrame, on='Type')
  .assign(String=lambda d: d['String']+' '+d['Thing'])
  [['String']]
)

print(out)

Output:

                  String
0         Jon likes Cats
1         Jon likes Dogs
2       Jon likes Tigers
3       Jon likes Llamas
4        Jon eats Apples
5         Jon eats Pears
6       Jon eats Bananas
7  Jon eats Strawberries

option 2

probably less efficient but more versatile, using the curly bracket notation to perform brace expansion (with the braceexpand module):

# pip install braceexpand
from braceexpand import braceexpand

mapper = ThingsDataFrame.groupby('Type')['Thing'].agg(','.join)

(StringDataFrame['String']
 .str.replace(r'(?<={)([^{}]*)(?=})', lambda m: mapper.get(m.group(1)))
 .apply(lambda x: list(braceexpand(x)))
 .explode()
)

NB. simplifying the StringDataFrame input to:

                String
0  Jon likes {animal}.
1    Jon eats {fruit}.

Output:

0           Jon likes Cats.
0           Jon likes Dogs.
0         Jon likes Tigers.
0         Jon likes Llamas.
1          Jon eats Apples.
1           Jon eats Pears.
1         Jon eats Bananas.
1    Jon eats Strawberries.
Name: String, dtype: object

This enables you to do funky stuff like:

print(StringDataFrame)
#                                  String
# 0  Jon likes {animal} that eat {fruit}.

print(ThingsDataFrame)
#     Thing    Type
# 0    Cats  animal
# 1    Dogs  animal
# 2  Apples   fruit
# 3   Pears   fruit

mapper = ThingsDataFrame.groupby('Type')['Thing'].agg(','.join)

(StringDataFrame['String']
 .str.replace(r'(?<={)([^{}]*)(?=})', lambda m: mapper.get(m.group(1)))
 .apply(lambda x: list(braceexpand(x)))
 .explode()
)

# 0    Jon likes Cats that eat Apples.
# 0     Jon likes Cats that eat Pears.
# 0    Jon likes Dogs that eat Apples.
# 0     Jon likes Dogs that eat Pears.
# Name: String, dtype: object