How to explode Python Pandas Dataframe based on string and criteria

Question

How to turn StringDataFrame:

String
Jon likes {ExplodeAnimals}.
Jon eats {ExplodeFruit}.

Into this:

String
Jon likes Cats.
Jon likes Dogs.
Jon likes Tigers.
Jon likes Llamas.
Jon eats Apples.
Jon eats Pears.
Jon eats Bananas.
Jon eats Strawberries.

Based on this ThingsDataFrame

Thing	Type
Cats	animal
Dogs	animal
Tigers	animal
Llamas	animal
Apples	fruit
Pears	fruit
Bananas	fruit
Strawberries	fruit

Answer 1

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