Get the maximum length of a word from a paragraph

I am working on a text problem where I have my pandas dataframe holding many columns out of which one consists of paragraphs. What I need in output are 3 columns as defined -

Length of largest words
Number of largest words (in case if there are any similar length)
Total number of such similar length words.

I account for a word if it is separated by a space.Looking for an answer using python apply-map.

Here's a sample input data -

df = pd.DataFrame({'text':[
    "that's not where the biggest opportunity is - it's with heart failure drug - very very huge market....",
    "Of course! I just got diagnosed with congestive heart failure and type 2 diabetes. I smoked for 12 years and ate like crap for about the same time. I quit smoking and have been on a diet for a few weeks now. Let me assure you that I'd rather have a coke, gummi bears, and a bag of cheez doodles than a pack of cigs right now. Addiction is addiction.",
    "STILLWATER, Okla. (AP) ? Medical examiner spokeswoman SpokesWoman: Oklahoma State player Tyrek Coger died of enlarged heart, manner of death ruled natural."
]})

df

    text                                                
0   that's not where the biggest opportunity is - ...   
1   Of course! I just got diagnosed with congestiv...   
2   STILLWATER, Okla. (AP) ? Medical examiner spok...

Here is the expected output -

    text                                               word_count   word_length     words
0   that's not where the biggest opportunity is - ...   1           11             opportunity
1   Of course! I just got diagnosed with congestiv...   1           10              congestive
2   STILLWATER, Okla. (AP) ? Medical examiner spok...   2           11              spokeswoman SpokesWoman

Solution

One possible solution using apply-map -

import nltk
import pandas as pd

# Reading df and proceeding with code

expanded_text = df.text.apply(lambda x: ' '.join(nltk.word_tokenize(x))).str.split(" ", expand=True)

df.word_length = expanded_text.applymap(lambda x: len(str(x)) if x != None else 0).max(axis=1)

i = 1
for idx, val in enumerate(expanded_text.itertuples()):
    temp = expanded_text.iloc[idx:idx + i, :].applymap(lambda x: True if len(str(x)) == df.loc[idx, 'word_length'] else False if x != None else False).T
    idx_ = temp.index[temp[idx] == True].values 
    words = " ".join(expanded_text.iloc[idx:idx + i, idx_].values.tolist()[0])
    df.loc[idx, 'words'] = words
    df.loc[idx, 'word_count'] = len(words.split())
    i += 1