I have tried out the following snippet of code for my project:
import pandas as pd
import nltk
from nltk.corpus import wordnet as wn
nltk.download('wordnet')
df=[]
hypo = wn.synset('science.n.01').hyponyms()
hyper = wn.synset('science.n.01').hypernyms()
mero = wn.synset('science.n.01').part_meronyms()
holo = wn.synset('science.n.01').part_holonyms()
ent = wn.synset('science.n.01').entailments()
df = df+hypo+hyper+mero+holo+ent
df_agri_clean = pd.DataFrame(df)
df_agri_clean.columns=["Items"]
print(df_agri_clean)
pd.set_option('display.expand_frame_repr', False)
It has given me this output of a dataframe:
Items
0 Synset('agrobiology.n.01')
1 Synset('agrology.n.01')
2 Synset('agronomy.n.01')
3 Synset('architectonics.n.01')
4 Synset('cognitive_science.n.01')
5 Synset('cryptanalysis.n.01')
6 Synset('information_science.n.01')
7 Synset('linguistics.n.01')
8 Synset('mathematics.n.01')
9 Synset('metallurgy.n.01')
10 Synset('metrology.n.01')
11 Synset('natural_history.n.01')
12 Synset('natural_science.n.01')
13 Synset('nutrition.n.03')
14 Synset('psychology.n.01')
15 Synset('social_science.n.01')
16 Synset('strategics.n.01')
17 Synset('systematics.n.01')
18 Synset('thanatology.n.01')
19 Synset('discipline.n.01')
20 Synset('scientific_theory.n.01')
21 Synset('scientific_knowledge.n.01')
This can be converted to a list by just printing df.
[Synset('agrobiology.n.01'), Synset('agrology.n.01'), Synset('agronomy.n.01'), Synset('architectonics.n.01'), Synset('cognitive_science.n.01'), Synset('cryptanalysis.n.01'), Synset('information_science.n.01'), Synset('linguistics.n.01'), Synset('mathematics.n.01'), Synset('metallurgy.n.01'), Synset('metrology.n.01'), Synset('natural_history.n.01'), Synset('natural_science.n.01'), Synset('nutrition.n.03'), Synset('psychology.n.01'), Synset('social_science.n.01'), Synset('strategics.n.01'), Synset('systematics.n.01'), Synset('thanatology.n.01'), Synset('discipline.n.01'), Synset('scientific_theory.n.01'), Synset('scientific_knowledge.n.01')]
I wish to change every word under "Items" like so :
Synset('agrobiology.n.01') => agrobiology.n.01
or
Synset('agrobiology.n.01') => 'agrobiology'
Any answer associated will be appreciated! Thanks!
To access the name of these items, just do function.name(). You could use line comprehension update these items as follows:
df_agri_clean['Items'] = [df_agri_clean['Items'][i].name() for i in range(len(df_agri_clean))]
df_agri_clean
The output will be as you expected
Items
0 agrobiology.n.01
1 agrology.n.01
2 agronomy.n.01
3 architectonics.n.01
4 cognitive_science.n.01
5 cryptanalysis.n.01
6 information_science.n.01
7 linguistics.n.01
8 mathematics.n.01
9 metallurgy.n.01
10 metrology.n.01
11 natural_history.n.01
12 natural_science.n.01
13 nutrition.n.03
14 psychology.n.01
15 social_science.n.01
16 strategics.n.01
17 systematics.n.01
18 thanatology.n.01
19 discipline.n.01
20 scientific_theory.n.01
21 scientific_knowledge.n.01
To further replace ".n.01" as well from the string, you could do the following:
df_agri_clean['Items'] = [df_agri_clean['Items'][i].name().replace('.n.01', '') for i in range(len(df_agri_clean))]
df_agri_clean
Output (just like your second expected output)
Items
0 agrobiology
1 agrology
2 agronomy
3 architectonics
4 cognitive_science
5 cryptanalysis
6 information_science
7 linguistics
8 mathematics
9 metallurgy
10 metrology
11 natural_history
12 natural_science
13 nutrition.n.03
14 psychology
15 social_science
16 strategics
17 systematics
18 thanatology
19 discipline
20 scientific_theory
21 scientific_knowledge