<jupyter_start><jupyter_text>Home Work Q1. Write a function that computes the volume of a sphere given its radius.The volume of a sphere is given as4/3x πxr**3<jupyter_code>def volume(rad):
    return (4 * 3.14 * (rad ** 3))/4
# Check
volume(2)<jupyter_output><empty_output><jupyter_text>Q2. Write a function that checks whether a number is in a given range (inclusive of high and low)<jupyter_code>def range_chk(num,low,high):
    if num >= low and num <= high : 
       return True
    return False
range_chk(21, 5,20)<jupyter_output><empty_output><jupyter_text>Q3. Write a Python function that accepts a string and calculates the number of upper case letters and lower case letters.Sample String : 'Hello Mr. Rogers, how are you this fine Tuesday?'Expected Output : No. of Upper case characters : 4No. of Lower case Characters : 33<jupyter_code>def up_low(sentence):
    upper = 0
    lower = 0
    for s in sentence :
        if s.isupper():
            upper = upper +1
        else :
            lower = lower + 1
    print ("Upper case ", upper)
    print ("Lower case ", lower)
    
up_low('aSDda')<jupyter_output>Upper case  2
Lower case  3<jupyter_text>Q4. Write a Python function to check whether a string is pangram or not.Note : Pangrams are words or sentences containing every letter of the alphabet at least once.For example : "The quick brown fox jumps over the lazy dog"<jupyter_code>def ispangram(str1):
    pass<jupyter_output><empty_output><jupyter_text>Q5. MASTER YODA: Given a sentence, return a sentence with the words reversedmaster_yoda('I am home') --> 'home am I'master_yoda('We are ready') --> 'ready are We'<jupyter_code>def master_yoda(text):
    pass<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09000584453535944, 'fraction_numerical': 0.017533606078316773, 'mean_word_length': 4.050147492625369, 'pattern_counts': {'":': 0, '<': 21, '<?xml version=': 0, '>': 23, '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': '5', 'dir': 'jupyter-structured-clean-dedup', 'id': '455475', 'license': 'MIT', 'n_tokens_mistral': 567, 'n_tokens_neox': 542, 'n_words': 200, 'path': 'Homework - ITM FCS .ipynb', 'repo_name': 'sumathi-kanthakumar/PythonITMFCS', 'size': '1711'}