<jupyter_start><jupyter_text>**Mean without using library**<jupyter_code>n_num = [1,2,3,4,5]
n = len(n_num)
get_sum = sum(n_num)
mean = get_sum / n
print("Mean: "+str(mean))<jupyter_output>Mean: 3.0<jupyter_text>Median without using library<jupyter_code>n_num = [1,2,3,4,5]
n = len(n_num)
n_num.sort()
if n % 2 == 0:
  median1 = n_num[n/2]
  median2 = n_num[n//2 - 1]
  median = (median1 + median2)/2
else:
  median = n_num[n//2]
print("Median: "+str(median))<jupyter_output>Median: 3<jupyter_text>**Mode without using library**<jupyter_code>from collections import Counter
n_num = [1,2,3,4,5,5]
n = len(n_num)
data = Counter(n_num)
get_mode = dict(data)
mode = [k for k, v in get_mode.items() if v == max(list(data.values()))]
if len(mode) == n:
  get_mode = "No mode found"
else:
  get_mode = "Mode: "+','.join(map(str,mode))
print(get_mode)<jupyter_output>Mode: 5<jupyter_text>**Mean, Median And Mode using library**<jupyter_code>import numpy
import statistics as stats
n_num = [1,2,3,4,8,9,6,7,9,5,6,6,2,5,2,5,5,3,3,2,2,2,2,2,2,2]
mean = numpy.mean(n_num)
print("Mean: "+str(mean))
median = numpy.median(n_num)
print("Median: "+str(median))
mode = stats.mode(n_num)
print("Mode: "+str(mode))
print("Standard Deviation: "+str(numpy.std(n_num)))
print("Varience: "+str(numpy.var(n_num)))<jupyter_output>Mean: 4.038461538461538
Median: 3.0
Mode: 2
Standard Deviation: 2.344892473027105
Varience: 5.4985207100591715
{'fraction_non_alphanumeric': 0.1872791519434629, 'fraction_numerical': 0.07703180212014134, 'mean_word_length': 6.955056179775281, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 13, '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': '4', 'dir': 'jupyter-structured-clean-dedup', 'id': '301660', 'license': 'Apache-2.0', 'n_tokens_mistral': 692, 'n_tokens_neox': 639, 'n_words': 116, 'path': 'DMDW_Lab_Assignment_01.ipynb', 'repo_name': '18CSE178/DMDW', 'size': '1415'}