<jupyter_start><jupyter_text>convert the paragrap into dictionary '''The call date records of <NAME> revealed that there were no calls or messages exchanged between <NAME> and the late actor, after <NAME>'s death. While this revelation has raised a lot of questions,Rhea's call date records are sure to grab your attention. According to Times Now's latest report, the 'Jalebi' actress had called Sushant nearly 94 times while received 51 calls from him.While the total calls exchanged between the two total up to 147 calls.'''<jupyter_code>dict1={}
def fun_str(string1):
    for item in string1.split():
        dict1[item]=string1.count(item)
    return dict1
string1=input("enter the string:")
string1=string1.lower()
fun_str(string1)<jupyter_output><empty_output><jupyter_text>convert into dictionary s = "id,name,age,act,room,dep\n1,Jack,68,T,13,8\n17,Betty,88,F,15,7"<jupyter_code>s = "id1,name,age,act,room,dep\n1,Jack,68,T,13,8\n17,Betty,88,F,15,7"
s.split()
a,b,c=s.split("\n")
a=a.split(",")
b=b.split(",")
c=c.split(",")
dict=dict(zip(a,(zip(b,c))))
dict
def solution(dict,category):
     for i in dict:
            if i == category:
                for j in dict[i]:
                    try:
                        if int(j):
                            return max(list(dict[i]))
                    except:
                        print("error")
                        break
category=input("enter the category:")
solution(dict,category)<jupyter_output>enter the category:act
error
error
{'fraction_non_alphanumeric': 0.12533333333333332, 'fraction_numerical': 0.029333333333333333, 'mean_word_length': 3.363372093023256, 'pattern_counts': {'":': 0, '<': 11, '<?xml version=': 0, '>': 11, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '402659', 'license': 'MIT', 'n_tokens_mistral': 508, 'n_tokens_neox': 476, 'n_words': 135, 'path': 'dict.ipynb', 'repo_name': 'AKSK16101999/technovative', 'size': '1530'}