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Write a Python program to find the nth Hamming number. User itertools module.

import itertools from heapq import merge def nth_hamming_number(n): def num_recur(): last = 1 yield last x, y, z = itertools.tee(num_recur(), 3) for n in merge((2 * i for i in x), (3 * i for i in y), (5 * i for i in z)): if n != last: yield n last = n result = itertools.islice(num_recur(), n) return list(result)[-1] print(nth_hamming_number(8)) print(nth_hamming_number(14)) print(nth_hamming_number(17))

Write a Python program to find the last occurrence of a specified item in a given list.

def last_occurrence(l1, ch): return ''.join(l1).rindex(ch) chars = ['s','d','f','s','d','f','s','f','k','o','p','i','w','e','k','c'] print("Original list:") print(chars) ch = 'f' print("Last occurrence of",ch,"in the said list:") print(last_occurrence(chars, ch)) ch = 'c' print("Last occurrence of",ch,"in the said list:") print(last_occurrence(chars, ch)) ch = 'k' print("Last occurrence of",ch,"in the said list:") print(last_occurrence(chars, ch)) ch = 'w' print("Last occurrence of",ch,"in the said list:") print(last_occurrence(chars, ch))

Write a Python program to convert Python dictionary object (sort by key) to JSON data. Print the object members with indent level 4.

import json j_str = {'4': 5, '6': 7, '1': 3, '2': 4} print("Original String:") print(j_str) print("\nJSON data:") print(json.dumps(j_str, sort_keys=True, indent=4))

Write a Python program to create the combinations of 3 digit combo.

numbers = [] for num in range(1000): num=str(num).zfill(3) print(num) numbers.append(num)

Write a Python program to create an iterator to get specified number of permutations of elements.

import itertools as it def permutations_data(iter, length): return it.permutations(iter, length) #List result = permutations_data(['A','B','C','D'], 3) print("\nIterator to get specified number of permutations of elements:") for i in result: print(i) #String result = permutations_data("Python", 2) print("\nIterator to get specified number of permutations of elements:") for i in result: print(i)

Write a Python function to get a string made of its first three characters of a specified string. If the length of the string is less than 3 then return the original string.

def first_three(str): return str[:3] if len(str) > 3 else str print(first_three('ipy')) print(first_three('python')) print(first_three('py'))

Write a Python program to get hourly datetime between two hours.

import arrow a = arrow.utcnow() print("Current datetime:") print(a) print("\nString representing the date, controlled by an explicit format string:") print(arrow.utcnow().strftime('%d-%m-%Y %H:%M:%S')) print(arrow.utcnow().strftime('%Y-%m-%d %H:%M:%S')) print(arrow.utcnow().strftime('%Y-%d-%m %H:%M:%S'))

Write a Python program to display formatted text (width=50) as output.

import textwrap sample_text = ''' Python is a widely used high-level, general-purpose, interpreted, dynamic programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than possible in languages such as C++ or Java. ''' print() print(textwrap.fill(sample_text, width=50)) print()

Write a Python function to find the maximum and minimum numbers from a sequence of numbers.

def max_min(data): l = data[0] s = data[0] for num in data: if num> l: l = num elif num< s: s = num return l, s print(max_min([0, 10, 15, 40, -5, 42, 17, 28, 75]))

Write a Pandas program to create a sequence of durations increasing by an hour.

import pandas as pd date_range = pd.timedelta_range(0, periods=49, freq='H') print("Hourly range of perods 49:") print(date_range)

Write a NumPy program to sort the specified number of elements from beginning of a given array.

import numpy as np nums = np.random.rand(10) print("Original array:") print(nums) print("\nSorted first 5 elements:") print(nums[np.argpartition(nums,range(5))])

Write a Python program to extract year, month, date and time using Lambda.

import datetime now = datetime.datetime.now() print(now) year = lambda x: x.year month = lambda x: x.month day = lambda x: x.day t = lambda x: x.time() print(year(now)) print(month(now)) print(day(now)) print(t(now))

Write a Python program to find all the common characters in lexicographical order from two given lower case strings. If there are no common letters print "No common characters".

from collections import Counter def common_chars(str1,str2): d1 = Counter(str1) d2 = Counter(str2) common_dict = d1 & d2 if len(common_dict) == 0: return "No common characters." # list of common elements common_chars = list(common_dict.elements()) common_chars = sorted(common_chars) return ''.join(common_chars) str1 = 'Python' str2 = 'PHP' print("Two strings: "+str1+' : '+str2) print(common_chars(str1, str2)) str1 = 'Java' str2 = 'PHP' print("Two strings: "+str1+' : '+str2) print(common_chars(str1, str2))

Write a Python program to remove a newline in Python.

str1='Python Exercises\n' print(str1) print(str1.rstrip())

Write a Pandas program to extract the column labels, shape and data types of the dataset (titanic.csv).

import pandas as pd import numpy as np df = pd.read_csv('titanic.csv') print("List of columns:") print(df.columns) print("\nShape of the Dataset:") print(df.shape) print("\nData types of the Dataset:") print(df.dtypes)

Write a Pandas program to replace arbitrary values with other values in a given DataFrame.

import pandas as pd df = pd.DataFrame({ 'company_code': ['A','B', 'C', 'D', 'A'], 'date_of_sale': ['12/05/2002','16/02/1999','25/09/1998','12/02/2022','15/09/1997'], 'sale_amount': [12348.5, 233331.2, 22.5, 2566552.0, 23.0] }) print("Original DataFrame:") print(df) print("\nReplace A with c:") df = df.replace("A", "C") print(df)

Write a NumPy program to calculate mean across dimension, in a 2D numpy array.

import numpy as np x = np.array([[10, 30], [20, 60]]) print("Original array:") print(x) print("Mean of each column:") print(x.mean(axis=0)) print("Mean of each row:") print(x.mean(axis=1))

Write a Pandas program to create a Pivot table and find survival rate by gender, age of the different categories of various classes. Add the fare as a dimension of columns and partition fare column into 2 categories based on the values present in fare columns.

import pandas as pd import numpy as np df = pd.read_csv('titanic.csv') fare = pd.qcut(df['fare'], 2) age = pd.cut(df['age'], [0, 10, 30, 60, 80]) result = df.pivot_table('survived', index=['sex', age], columns=[fare, 'pclass']) print(result)

Write a Python program to retrieve the value of the nested key indicated by the given selector list from a dictionary or list.

from functools import reduce from operator import getitem def get(d, selectors): return reduce(getitem, selectors, d) users = { 'freddy': { 'name': { 'first': 'Fateh', 'last': 'Harwood' }, 'postIds': [1, 2, 3] } } print(get(users, ['freddy', 'name', 'last'])) print(get(users, ['freddy', 'postIds', 1]))

Write a Python program to sort unsorted numbers using Recursive Bubble Sort.

#Ref.https://bit.ly/3oneU2l def bubble_sort(list_data: list, length: int = 0) -> list: length = length or len(list_data) swapped = False for i in range(length - 1): if list_data[i] > list_data[i + 1]: list_data[i], list_data[i + 1] = list_data[i + 1], list_data[i] swapped = True return list_data if not swapped else bubble_sort(list_data, length - 1) nums = [4, 3, 5, 1, 2] print("\nOriginal list:") print(nums) print("After applying Recursive Insertion Sort the said list becomes:") bubble_sort(nums, len(nums)) print(nums) nums = [5, 9, 10, 3, -4, 5, 178, 92, 46, -18, 0, 7] print("\nOriginal list:") print(nums) print("After applying Recursive Bubble Sort the said list becomes:") bubble_sort(nums, len(nums)) print(nums) nums = [1.1, 1, 0, -1, -1.1, .1] print("\nOriginal list:") print(nums) print("After applying Recursive Bubble Sort the said list becomes:") bubble_sort(nums, len(nums)) print(nums) nums = ['z','a','y','b','x','c'] print("\nOriginal list:") print(nums) print("After applying Recursive Bubble Sort the said list becomes:") bubble_sort(nums, len(nums)) print(nums)

Write a Python program to count the values associated with key in a dictionary.

student = [{'id': 1, 'success': True, 'name': 'Lary'}, {'id': 2, 'success': False, 'name': 'Rabi'}, {'id': 3, 'success': True, 'name': 'Alex'}] print(sum(d['id'] for d in student)) print(sum(d['success'] for d in student))

Write a NumPy program to multiply an array of dimension (2,2,3) by an array with dimensions (2,2).

import numpy as np nums1 = np.ones((2,2,3)) nums2 = 3*np.ones((2,2)) print("Original array:") print(nums1) new_array = nums1 * nums2[:,:,None] print("\nNew array:") print(new_array)

Write a NumPy program to swap rows and columns of a given array in reverse order.

import numpy as np nums = np.array([[[1, 2, 3, 4], [0, 1, 3, 4], [90, 91, 93, 94], [5, 0, 3, 2]]]) print("Original array:") print(nums) print("\nSwap rows and columns of the said array in reverse order:") new_nums = print(nums[::-1, ::-1]) print(new_nums)

Write a NumPy program to create an 1-D array of 20 elements. Now create a new array of shape (5, 4) from the said array, then restores the reshaped array into a 1-D array.

import numpy as np array_nums = np.arange(0, 40, 2) print("Original array:") print(array_nums) print("\nNew array of shape(5, 4):") new_array = array_nums.reshape(5, 4) print(new_array) print("\nRestore the reshaped array into a 1-D array:") print(new_array.flatten())

Write a Python program to sort a list of elements using Tree sort.

# License https://bit.ly/2InTS3W # Tree_sort algorithm # Build a BST and in order traverse. class node(): # BST data structure def __init__(self, val): self.val = val self.left = None self.right = None def insert(self,val): if self.val: if val < self.val: if self.left is None: self.left = node(val) else: self.left.insert(val) elif val > self.val: if self.right is None: self.right = node(val) else: self.right.insert(val) else: self.val = val def inorder(root, res): # Recursive travesal if root: inorder(root.left,res) res.append(root.val) inorder(root.right,res) def treesort(arr): # Build BST if len(arr) == 0: return arr root = node(arr[0]) for i in range(1,len(arr)): root.insert(arr[i]) # Traverse BST in order. res = [] inorder(root,res) return res print(treesort([7,1,5,2,19,14,17]))

Write a NumPy program to create an element-wise comparison (equal, equal within a tolerance) of two given arrays.

import numpy as np x = np.array([72, 79, 85, 90, 150, -135, 120, -10, 60, 100]) y = np.array([72, 79, 85, 90, 150, -135, 120, -10, 60, 100.000001]) print("Original numbers:") print(x) print(y) print("Comparison - equal:") print(np.equal(x, y)) print("Comparison - equal within a tolerance:") print(np.allclose(x, y))

Write a Pandas program to split a given dataframe into groups with multiple aggregations.

import pandas as pd pd.set_option('display.max_rows', None) #pd.set_option('display.max_columns', None) df = pd.DataFrame({ 'school_code': ['s001','s002','s003','s001','s002','s001'], 'class': ['V', 'V', 'VI', 'VI', 'V', 'VI'], 'name': ['Alberto Franco','Gino Mcneill','Ryan Parkes', 'Eesha Hinton', 'Gino Mcneill', 'David Parkes'], 'date_Of_Birth ': ['15/05/2002','17/05/2002','16/02/1999','25/09/1998','11/05/2002','15/09/1997'], 'age': [12, 12, 13, 13, 14, 12], 'height': [173, 192, 186, 167, 151, 159], 'weight': [35, 32, 33, 30, 31, 32], 'address': ['street1', 'street2', 'street3', 'street1', 'street2', 'street4']}, index=['S1', 'S2', 'S3', 'S4', 'S5', 'S6']) print("Original DataFrame:") print(df) print("\nGroup by with multiple aggregations:") result = df.groupby(['school_code','class']).agg({'height': ['max', 'mean'], 'weight': ['sum','min','count']}) print(result)

Write a NumPy program to find a matrix or vector norm.

import numpy as np v = np.arange(7) result = np.linalg.norm(v) print("Vector norm:") print(result) m = np.matrix('1, 2; 3, 4') result1 = np.linalg.norm(m) print("Matrix norm:") print(result1)

Write a Python program to delete the first item from a singly linked list.

class Node: # Singly linked node def __init__(self, data=None): self.data = data self.next = None class singly_linked_list: def __init__(self): # Createe an empty list self.tail = None self.head = None self.count = 0 def append_item(self, data): #Append items on the list node = Node(data) if self.head: self.head.next = node self.head = node else: self.tail = node self.head = node self.count += 1 def delete_item(self, data): # Delete an item from the list current = self.tail prev = self.tail while current: if current.data == data: if current == self.tail: self.tail = current.next else: prev.next = current.next self.count -= 1 return prev = current current = current.next def iterate_item(self): # Iterate the list. current_item = self.tail while current_item: val = current_item.data current_item = current_item.next yield val items = singly_linked_list() items.append_item('PHP') items.append_item('Python') items.append_item('C#') items.append_item('C++') items.append_item('Java') print("Original list:") for val in items.iterate_item(): print(val) print("\nAfter removing the first item from the list:") items.delete_item('PHP') for val in items.iterate_item(): print(val)

Write a Python program to find the difference between two list including duplicate elements. Use collections module.

from collections import Counter l1 = [1,1,2,3,3,4,4,5,6,7] l2 = [1,1,2,4,5,6] print("Original lists:") c1 = Counter(l1) c2 = Counter(l2) diff = c1-c2 print(list(diff.elements()))

Write a Python function that takes a positive integer and returns the sum of the cube of all the positive integers smaller than the specified number.

def sum_of_cubes(n): n -= 1 total = 0 while n > 0: total += n * n * n n -= 1 return total print("Sum of cubes smaller than the specified number: ",sum_of_cubes(3))

Write a Pandas program to import excel data (coalpublic2013.xlsx ) into a Pandas dataframe and find a list of specified customers by name.

import pandas as pd import numpy as np df = pd.read_excel('E:\coalpublic2013.xlsx') df.query('Mine_Name == ["Shoal Creek Mine", "Piney Woods Preparation Plant"]').head()

Write a Python program to create a new Arrow object, cloned from the current one.

import arrow a = arrow.utcnow() print("Current datetime:") print(a) cloned = a.clone() print("\nCloned datetime:") print(cloned)

Write a NumPy program to create a 3-D array with ones on a diagonal and zeros elsewhere.

import numpy as np x = np.eye(3) print(x)

Write a NumPy program to extract first element of the second row and fourth element of fourth row from a given (4x4) array.

import numpy as np arra_data = np.arange(0,16).reshape((4, 4)) print("Original array:") print(arra_data) print("\nExtracted data: First element of the second row and fourth element of fourth row ") print(arra_data[[1,3], [0,3]])

Write a Python program to get date and time properties from datetime function using arrow module.

import arrow a = arrow.utcnow() print("Current date:") print(a.date()) print("\nCurrent time:") print(a.time())

Write a Python program to get the size of a file.

import os file_size = os.path.getsize("abc.txt") print("\nThe size of abc.txt is :",file_size,"Bytes") print()

Create a dataframe of ten rows, four columns with random values. Write a Pandas program to display bar charts in dataframe on specified columns.

import pandas as pd import numpy as np np.random.seed(24) df = pd.DataFrame({'A': np.linspace(1, 10, 10)}) df = pd.concat([df, pd.DataFrame(np.random.randn(10, 4), columns=list('BCDE'))], axis=1) df.iloc[0, 2] = np.nan df.iloc[3, 3] = np.nan df.iloc[4, 1] = np.nan df.iloc[9, 4] = np.nan print("Original array:") print(df) print("\nBar charts in dataframe:") df.style.bar(subset=['B', 'C'], color='#d65f5f')

Write a Pandas program to create a graphical analysis of UFO (unidentified flying object) sighted by month.

import pandas as pd import matplotlib.pyplot as plt import seaborn as sns df = pd.read_csv(r'ufo.csv') df['Date_time'] = df['Date_time'].astype('datetime64[ns]') df["ufo_yr"] = df.Date_time.dt.month months_data = df.ufo_yr.value_counts() months_index = months_data.index # x ticks months_values = months_data.get_values() plt.figure(figsize=(15,8)) plt.xticks(rotation = 60) plt.title('UFO sighted by Month') plt.xlabel("Months") plt.ylabel("Number of sighting") months_plot = sns.barplot(x=months_index[:60],y=months_values[:60], palette = "Oranges")

Write a Python program to sort unsorted numbers using Recursive Quick Sort.

def quick_sort(nums: list) -> list: if len(nums) <= 1: return nums else: return ( quick_sort([el for el in nums[1:] if el <= nums[0]]) + [nums[0]] + quick_sort([el for el in nums[1:] if el > nums[0]]) ) nums = [4, 3, 5, 1, 2] print("\nOriginal list:") print(nums) print("After applying Recursive Quick Sort the said list becomes:") print(quick_sort(nums)) nums = [5, 9, 10, 3, -4, 5, 178, 92, 46, -18, 0, 7] print("\nOriginal list:") print(nums) print("After applying Recursive Quick Sort the said list becomes:") print(quick_sort(nums)) nums = [1.1, 1, 0, -1, -1.1, .1] print("\nOriginal list:") print(nums) print("After applying Recursive Quick Sort the said list becomes:") print(quick_sort(nums))

Write a Python program to convert timezone from local to utc, utc to local or specified zones.

import arrow utc = arrow.utcnow() print("utc:") print(utc) print("\nutc to local:") print(utc.to('local')) print("\nlocal to utc:") print(utc.to('local').to('utc')) print("\nutc to specific location:") print(utc.to('US/Pacific'))

Write a Python program to find the difference between two list including duplicate elements.

def list_difference(l1,l2): result = list(l1) for el in l2: result.remove(el) return result l1 = [1,1,2,3,3,4,4,5,6,7] l2 = [1,1,2,4,5,6] print("Original lists:") print(l1) print(l2) print("\nDifference between two said list including duplicate elements):") print(list_difference(l1,l2))

Create a dataframe of ten rows, four columns with random values. Write a Pandas program to display the dataframe in Heatmap style.

import pandas as pd import numpy as np import seaborn as sns np.random.seed(24) df = pd.DataFrame({'A': np.linspace(1, 10, 10)}) df = pd.concat([df, pd.DataFrame(np.random.randn(10, 4), columns=list('BCDE'))], axis=1) print("Original array:") print(df) print("\nDataframe - Heatmap style:") cm = sns.light_palette("red", as_cmap=True) df.style.background_gradient(cmap='viridis')

Write a Python program to remove a tag from a given tree of html document and destroy it and its contents.

from bs4 import BeautifulSoup html_content = '<a href="https://w3resource.com/">Python exercises<i>w3resource</i></a>' soup = BeautifulSoup(html_content, "lxml") print("Original Markup:") a_tag = soup.a print(a_tag) new_tag = soup.a.decompose() print("After decomposing:") print(new_tag)

Write a Python program to convert a given number (integer) to a list of digits.

def digitize(n): return list(map(int, str(n))) print(digitize(123)) print(digitize(1347823))

rite a Python program that accepts a sequence of lines (blank line to terminate) as input and prints the lines as output (all characters in lower case).

lines = [] while True: l = input() if l: lines.append(l.upper()) else: break; for l in lines: print(l)

Write a Python program to remove a tag or string from a given tree of html document and replace it with the given tag or string.

from bs4 import BeautifulSoup html_markup= '<a href="https://w3resource.com/">Python exercises<i>w3resource</i></a>' soup = BeautifulSoup(html_markup, "lxml") print("Original markup:") a_tag = soup.a print(a_tag) new_tag = soup.new_tag("b") new_tag.string = "PHP" b_tag = a_tag.i.replace_with(new_tag) print("New Markup:") print(a_tag)

Write a Pandas program to extract the unique sentences from a given column of a given DataFrame.

import pandas as pd import re as re df = pd.DataFrame({ 'company_code': ['Abcd','EFGF', 'zefsalf', 'sdfslew', 'zekfsdf'], 'date_of_sale': ['12/05/2002','16/02/1999','05/09/1998','12/02/2022','15/09/1997'], 'address': ['9910 Surrey Avenue\n9910 Surrey Avenue','92 N. Bishop Avenue','9910 Golden Star Avenue', '102 Dunbar St.\n102 Dunbar St.', '17 West Livingston Court'] }) print("Original DataFrame:") print(df) def find_unique_sentence(str1): result = re.findall(r'(?sm)(^[^\r\n]+$)(?!.*^\1$)', str1) return result df['unique_sentence']=df['address'].apply(lambda st : find_unique_sentence(st)) print("\nExtract unique sentences :") print(df)

Write a Pandas program to filter all records where the average consumption of beverages per person from .5 to 2.50 in world alcohol consumption dataset.

import pandas as pd # World alcohol consumption data w_a_con = pd.read_csv('world_alcohol.csv') print("World alcohol consumption sample data:") print(w_a_con.head()) print("\nFilter all records where the average consumption of beverages per person from .5 to 2.50.:") print(w_a_con[(w_a_con['Display Value'] < 2.5) & (w_a_con['Display Value']>.5)].head())

Write a Pandas program to extract elements in the given positional indices along an axis of a dataframe.

import pandas as pd import numpy as np sales_arrays = [['sale1', 'sale1', 'sale3', 'sale3', 'sale2', 'sale2', 'sale4', 'sale4'], ['city1', 'city2', 'city1', 'city2', 'city1', 'city2', 'city1', 'city2']] sales_tuples = list(zip(*sales_arrays)) sales_index = pd.MultiIndex.from_tuples(sales_tuples, names=['sale', 'city']) print("\nConstruct a Dataframe using the said MultiIndex levels:") df = pd.DataFrame(np.random.randn(8, 5), index=sales_index) print(df) print("\nSelect 1st, 2nd and 3rd row of the said DataFrame:") positions = [1, 2, 5] print(df.take([1, 2, 5])) print("\nTake elements at indices 1 and 2 along the axis 1 (column selection):") print(df.take([1, 2], axis=1)) print("\nTake elements at indices 4 and 3 using negative integers along the axis 1 (column selection):") print(df.take([-1, -2], axis=1))

Write a Python program to find a pair with highest product from a given array of integers.

def max_Product(arr): arr_len = len(arr) if (arr_len < 2): print("No pairs exists") return # Initialize max product pair x = arr[0]; y = arr[1] # Traverse through every possible pair for i in range(0, arr_len): for j in range(i + 1, arr_len): if (arr[i] * arr[j] > x * y): x = arr[i]; y = arr[j] return x,y nums = [1, 2, 3, 4, 7, 0, 8, 4] print("Original array:", nums) print("Maximum product pair is:", max_Product(nums)) nums = [0, -1, -2, -4, 5, 0, -6] print("\nOriginal array:", nums) print("Maximum product pair is:", max_Product(nums))

Write a Python program to move all zero digits to end of a given list of numbers.

def test(lst): result = sorted(lst, key=lambda x: not x) return result nums = [3,4,0,0,0,6,2,0,6,7,6,0,0,0,9,10,7,4,4,5,3,0,0,2,9,7,1] print("\nOriginal list:") print(nums) print("\nMove all zero digits to end of the said list of numbers:") print(test(nums))

Write a NumPy program to compute cross-correlation of two given arrays.

import numpy as np x = np.array([0, 1, 3]) y = np.array([2, 4, 5]) print("\nOriginal array1:") print(x) print("\nOriginal array1:") print(y) print("\nCross-correlation of the said arrays:\n",np.cov(x, y))

Write a Python program to get the actual module object for a given object.

from inspect import getmodule from math import sqrt print(getmodule(sqrt))

Write a Python program to extract the nth element from a given list of tuples using lambda.

def extract_nth_element(test_list, n): result = list(map (lambda x:(x[n]), test_list)) return result students = [('Greyson Fulton', 98, 99), ('Brady Kent', 97, 96), ('Wyatt Knott', 91, 94), ('Beau Turnbull', 94, 98)] print ("Original list:") print(students) n = 0 print("\nExtract nth element ( n =",n,") from the said list of tuples:") print(extract_nth_element(students, n)) n = 2 print("\nExtract nth element ( n =",n,") from the said list of tuples:") print(extract_nth_element(students, n))

Write a NumPy program to add an extra column to a NumPy array.

import numpy as np x = np.array([[10,20,30], [40,50,60]]) y = np.array([[100], [200]]) print(np.append(x, y, axis=1))

Write a Python program to calculate the product of a given list of numbers using lambda.

import functools def remove_duplicates(nums): result = functools.reduce(lambda x, y: x * y, nums, 1) return result nums1 = [1,2,3,4,5,6,7,8,9,10] nums2 = [2.2,4.12,6.6,8.1,8.3] print("list1:", nums1) print("Product of the said list numbers:") print(remove_duplicates(nums1)) print("\nlist2:", nums2) print("Product of the said list numbers:") print(remove_duplicates(nums2))

Write a Python program to parse a string representing a time according to a format.

import arrow a = arrow.utcnow() print("Current datetime:") print(a) print("\ntime.struct_time, in the current timezone:") print(arrow.utcnow().timetuple())

Write a NumPy program to create a random 10x4 array and extract the first five rows of the array and store them into a variable.

import numpy as np x = np.random.rand(10, 4) print("Original array: ") print(x) y= x[:5, :] print("First 5 rows of the above array:") print(y)

Write a Pandas program to find average consumption of wine per person greater than 2 in world alcohol consumption dataset.

import pandas as pd # World alcohol consumption data w_a_con = pd.read_csv('world_alcohol.csv') print("World alcohol consumption sample data:") print(w_a_con.head()) print("\nAverage consumption of wine per person greater than 2:") print(w_a_con[(w_a_con['Beverage Types'] == 'Wine') & (w_a_con['Display Value'] > .2)].count())

Write a Pandas program to convert Series of lists to one Series.

import pandas as pd s = pd.Series([ ['Red', 'Green', 'White'], ['Red', 'Black'], ['Yellow']]) print("Original Series of list") print(s) s = s.apply(pd.Series).stack().reset_index(drop=True) print("One Series") print(s)

Write a Python program to sort a list of elements using Time sort.

# License https://bit.ly/2InTS3W def binary_search(lst, item, start, end): if start == end: if lst[start] > item: return start else: return start + 1 if start > end: return start mid = (start + end) // 2 if lst[mid] < item: return binary_search(lst, item, mid + 1, end) elif lst[mid] > item: return binary_search(lst, item, start, mid - 1) else: return mid def insertion_sort(lst): length = len(lst) for index in range(1, length): value = lst[index] pos = binary_search(lst, value, 0, index - 1) lst = lst[:pos] + [value] + lst[pos:index] + lst[index+1:] return lst def merge(left, right): if not left: return right if not right: return left if left[0] < right[0]: return [left[0]] + merge(left[1:], right) return [right[0]] + merge(left, right[1:]) def time_sort(lst): runs, sorted_runs = [], [] length = len(lst) new_run = [lst[0]] sorted_array = [] for i in range(1, length): if i == length - 1: new_run.append(lst[i]) runs.append(new_run) break if lst[i] < lst[i - 1]: if not new_run: runs.append([lst[i - 1]]) new_run.append(lst[i]) else: runs.append(new_run) new_run = [] else: new_run.append(lst[i]) for run in runs: sorted_runs.append(insertion_sort(run)) for run in sorted_runs: sorted_array = merge(sorted_array, run) return sorted_array user_input = input("Input numbers separated by a comma:\n").strip() nums = [int(item) for item in user_input.split(',')] print(time_sort(nums))

Write a Python program to convert timezone from local to utc, utc to local or specified zones.

import arrow utc = arrow.utcnow() print("utc:") print(utc) print("\nutc to local:") print(utc.to('local')) print("\nlocal to utc:") print(utc.to('local').to('utc')) print("\nutc to specific location:") print(utc.to('US/Pacific'))

Write a NumPy program to subtract the mean of each row of a given matrix.

import numpy as np print("Original matrix:\n") X = np.random.rand(5, 10) print(X) print("\nSubtract the mean of each row of the said matrix:\n") Y = X - X.mean(axis=1, keepdims=True) print(Y)

Write a NumPy program to test whether two arrays are element-wise equal within a tolerance.

import numpy as np print("Test if two arrays are element-wise equal within a tolerance:") print(np.allclose([1e10,1e-7], [1.00001e10,1e-8])) print(np.allclose([1e10,1e-8], [1.00001e10,1e-9])) print(np.allclose([1e10,1e-8], [1.0001e10,1e-9])) print(np.allclose([1.0, np.nan], [1.0, np.nan])) print(np.allclose([1.0, np.nan], [1.0, np.nan], equal_nan=True))

Write a Pandas program to create a Pivot table and count the manager wise sale and mean value of sale amount.

import pandas as pd import numpy as np df = pd.read_excel('E:\SaleData.xlsx') print(pd.pivot_table(df,index=["Manager"],values=["Sale_amt"],aggfunc=[np.mean,len]))

Write a Python program to select all the Sundays of a specified year.

from datetime import date, timedelta def all_sundays(year): # January 1st of the given year dt = date(year, 1, 1) # First Sunday of the given year dt += timedelta(days = 6 - dt.weekday()) while dt.year == year: yield dt dt += timedelta(days = 7) for s in all_sundays(2020): print(s)

Write a Pandas program to print a concise summary of the dataset (titanic.csv).

import pandas as pd import numpy as np df = pd.read_csv('titanic.csv') result = df.info() print(result)

Write a Python program to create an object for writing and iterate over the rows to print the values.

import csv import sys with open('temp.csv', 'wt') as f: writer = csv.writer(f) writer.writerow(('id1', 'id2', 'date')) for i in range(3): row = ( i + 1, chr(ord('a') + i), '01/{:02d}/2019'.format(i + 1),) writer.writerow(row) print(open('temp.csv', 'rt').read())

Write a Python program to remove duplicate dictionary from a given list.

def remove_duplicate_dictionary(list_color): result = [dict(e) for e in {tuple(d.items()) for d in list_color}] return result list_color = [{'Green': '#008000'}, {'Black': '#000000'}, {'Blue': '#0000FF'}, {'Green': '#008000'}] print ("Original list with duplicate dictionary:") print(list_color) print("\nAfter removing duplicate dictionary of the said list:") print(remove_duplicate_dictionary(list_color))

Write a Pandas program to create a Pivot table and compute survival totals of all classes along each group.

import pandas as pd import numpy as np df = pd.read_csv('titanic.csv') result = df.pivot_table('survived', index='sex', columns='class', margins=True) print(result)

Write a Python program to remove first specified number of elements from a given list satisfying a condition.

def condition_match(x): return ((x % 2) == 0) def remove_items_con(data, N): ctr = 1 result = [] for x in data: if ctr > N or not condition_match(x): result.append(x) else: ctr = ctr + 1 return result nums = [3,10,4,7,5,7,8,3,3,4,5,9,3,4,9,8,5] N = 4 print("Original list:") print(nums) print("\nRemove first 4 even numbers from the said list:") print(remove_items_con(nums, N))

Write a Python program to convert a list of multiple integers into a single integer.

L = [11, 33, 50] print("Original List: ",L) x = int("".join(map(str, L))) print("Single Integer: ",x)

Write a Python program to find the value of the last element in the given list that satisfies the provided testing function.

def find_last(lst, fn): return next(x for x in lst[::-1] if fn(x)) print(find_last([1, 2, 3, 4], lambda n: n % 2 == 1)) print(find_last([1, 2, 3, 4], lambda n: n % 2 == 0))

Write a Python program to change the position of every n-th value with the (n+1)th in a list.

from itertools import zip_longest, chain, tee def replace2copy(lst): lst1, lst2 = tee(iter(lst), 2) return list(chain.from_iterable(zip_longest(lst[1::2], lst[::2]))) n = [0,1,2,3,4,5] print(replace2copy(n))

Write a Python program to multiply all the numbers in a given list using lambda.

from functools import reduce def mutiple_list(nums): result = reduce(lambda x, y: x*y, nums) return result nums = [4, 3, 2, 2, -1, 18] print ("Original list: ") print(nums) print("Mmultiply all the numbers of the said list:",mutiple_list(nums)) nums = [2, 4, 8, 8, 3, 2, 9] print ("\nOriginal list: ") print(nums) print("Mmultiply all the numbers of the said list:",mutiple_list(nums))

Write a Python program to remove unwanted characters from a given string.

def remove_chars(str1, unwanted_chars): for i in unwanted_chars: str1 = str1.replace(i, '') return str1 str1 = "Pyth*^on Exercis^es" str2 = "A%^!B#*CD" unwanted_chars = ["#", "*", "!", "^", "%"] print ("Original String : " + str1) print("After removing unwanted characters:") print(remove_chars(str1, unwanted_chars)) print ("\nOriginal String : " + str2) print("After removing unwanted characters:") print(remove_chars(str2, unwanted_chars))

Write a Python program to compute the average of n

import itertools as it nums = [[0, 1, 2], [2, 3, 4], [3, 4, 5, 6], [7, 8, 9, 10, 11], [12, 13, 14]] print("Original list:") print(nums) def get_avg(x): x = [i for i in x if i is not None] return sum(x, 0.0) / len(x) result = map(get_avg, it.zip_longest(*nums)) print("\nAverage of n-th elements in the said list of lists with different lengths:") print(list(result))

Write a Python program to find the details of a given zip code using Nominatim API and GeoPy package.

from geopy.geocoders import Nominatim geolocator = Nominatim(user_agent="geoapiExercises") zipcode1 = "99501" print("\nZipcode:",zipcode1) location = geolocator.geocode(zipcode1) print("Details of the said pincode:") print(location.address) zipcode2 = "CA9 3HX" print("\nZipcode:",zipcode2) location = geolocator.geocode(zipcode2) print("Details of the said pincode:") print(location.address) zipcode3 = "61000" print("\nZipcode:",zipcode3) location = geolocator.geocode(zipcode3) print("Details of the said pincode:") print(location.address) zipcode4 = "713101" print("\nZipcode:",zipcode4) location = geolocator.geocode(zipcode4) print("Details of the said pincode:") print(location.address)

Write a NumPy program to insert a space between characters of all the elements of a given array.

import numpy as np x = np.array(['python exercises', 'PHP', 'java', 'C++'], dtype=np.str) print("Original Array:") print(x) r = np.char.join(" ", x) print(r)

Write a Python program to merge some list items in given list using index value.

def merge_some_chars(lst,merge_from,merge_to): result = lst result[merge_from:merge_to] = [''.join(result[merge_from:merge_to])] return result chars = ['a', 'b', 'c', 'd', 'e', 'f', 'g'] print("Original lists:") print(chars) merge_from = 2 merge_to = 4 print("\nMerge items from",merge_from,"to",merge_to,"in the said List:") print(merge_some_chars(chars,merge_from,merge_to)) chars = ['a', 'b', 'c', 'd', 'e', 'f', 'g'] merge_from = 3 merge_to = 7 print("\nMerge items from",merge_from,"to",merge_to,"in the said List:") print(merge_some_chars(chars,merge_from,merge_to))

Write a Python function to check whether a number is perfect or not.

def perfect_number(n): sum = 0 for x in range(1, n): if n % x == 0: sum += x return sum == n print(perfect_number(6))

Write a Pandas program to split a given dataset, group by two columns and convert other columns of the dataframe into a dictionary with column header as key.

import pandas as pd pd.set_option('display.max_rows', None) pd.set_option('display.max_columns', None) df = pd.DataFrame({ 'school_code': ['s001','s002','s003','s001','s002','s004'], 'class': ['V', 'V', 'VI', 'VI', 'V', 'VI'], 'name': ['Alberto Franco','Gino Mcneill','Ryan Parkes', 'Eesha Hinton', 'Gino Mcneill', 'David Parkes'], 'date_Of_Birth ': ['15/05/2002','17/05/2002','16/02/1999','25/09/1998','11/05/2002','15/09/1997'], 'age': [12, 12, 13, 13, 14, 12], 'height': [173, 192, 186, 167, 151, 159], 'weight': [35, 32, 33, 30, 31, 32], 'address': ['street1', 'street2', 'street3', 'street1', 'street2', 'street4']}, index=['S1', 'S2', 'S3', 'S4', 'S5', 'S6']) print("Original DataFrame:") print(df) dict_data_list = list() for gg, dd in df.groupby(['school_code','class']): group = dict(zip(['school_code','class'], gg)) ocolumns_list = list() for _, data in dd.iterrows(): data = data.drop(labels=['school_code','class']) ocolumns_list.append(data.to_dict()) group['other_columns'] = ocolumns_list dict_data_list.append(group) print(dict_data_list)

Write a Python program to find the most common elements and their counts of a specified text.

from collections import Counter s = 'lkseropewdssafsdfafkpwe' print("Original string: "+s) print("Most common three characters of the said string:") print(Counter(s).most_common(3))

Write a NumPy program to round array elements to the given number of decimals.

import numpy as np x = np.round([1.45, 1.50, 1.55]) print(x) x = np.round([0.28, .50, .64], decimals=1) print(x) x = np.round([.5, 1.5, 2.5, 3.5, 4.5]) # rounds to nearest even value print(x)

Write a Pandas program to find the index of the first occurrence of the smallest and largest value of a given series.

import pandas as pd nums = pd.Series([1, 3, 7, 12, 88, 23, 3, 1, 9, 0]) print("Original Series:") print(nums) print("Index of the first occurrence of the smallest and largest value of the said series:") print(nums.idxmin()) print(nums.idxmax())

Write a NumPy program to generate a random number between 0 and 1.

import numpy as np rand_num = np.random.normal(0,1,1) print("Random number between 0 and 1:") print(rand_num)

Write a Python program to count number of unique sublists within a given list.

def unique_sublists(input_list): result ={} for l in input_list: result.setdefault(tuple(l), list()).append(1) for a, b in result.items(): result[a] = sum(b) return result list1 = [[1, 3], [5, 7], [1, 3], [13, 15, 17], [5, 7], [9, 11]] print("Original list:") print(list1) print("Number of unique lists of the said list:") print(unique_sublists(list1)) color1 = [["green", "orange"], ["black"], ["green", "orange"], ["white"]] print("\nOriginal list:") print(color1) print("Number of unique lists of the said list:") print(unique_sublists(color1))

Write a Python program to calculate the time runs (difference between start and current time) of a program.

from timeit import default_timer def timer(n): start = default_timer() # some code here for row in range(0,n): print(row) print(default_timer() - start) timer(5) timer(15)

Write a Python program to concatenate element-wise three given lists.

def concatenate_lists(l1,l2,l3): return [i + j + k for i, j, k in zip(l1, l2, l3)] l1 = ['0','1','2','3','4'] l2 = ['red','green','black','blue','white'] l3 = ['100','200','300','400','500'] print("Original lists:") print(l1) print(l2) print(l3) print("\nConcatenate element-wise three said lists:") print(concatenate_lists(l1,l2,l3))

Write a Python program to delete a specific row from a given SQLite table.

import sqlite3 from sqlite3 import Error def sql_connection(): try: conn = sqlite3.connect('mydatabase.db') return conn except Error: print(Error) def sql_table(conn): cursorObj = conn.cursor() # Create the table cursorObj.execute("CREATE TABLE salesman(salesman_id n(5), name char(30), city char(35), commission decimal(7,2));") # Insert records cursorObj.executescript(""" INSERT INTO salesman VALUES(5001,'James Hoog', 'New York', 0.15); INSERT INTO salesman VALUES(5002,'Nail Knite', 'Paris', 0.25); INSERT INTO salesman VALUES(5003,'Pit Alex', 'London', 0.15); INSERT INTO salesman VALUES(5004,'Mc Lyon', 'Paris', 0.35); INSERT INTO salesman VALUES(5005,'Paul Adam', 'Rome', 0.45); """) cursorObj.execute("SELECT * FROM salesman") rows = cursorObj.fetchall() print("Agent details:") for row in rows: print(row) print("\nDelete Salesman of ID 5003:") s_id = 5003 cursorObj.execute(""" DELETE FROM salesman WHERE salesman_id = ? """, (s_id,)) conn.commit() cursorObj.execute("SELECT * FROM salesman") rows = cursorObj.fetchall() print("\nAfter updating Agent details:") for row in rows: print(row) sqllite_conn = sql_connection() sql_table(sqllite_conn) if (sqllite_conn): sqllite_conn.close() print("\nThe SQLite connection is closed.")

Write a Python program to find the list with maximum and minimum length using lambda.

def max_length_list(input_list): max_length = max(len(x) for x in input_list ) max_list = max(input_list, key = lambda i: len(i)) return(max_length, max_list) def min_length_list(input_list): min_length = min(len(x) for x in input_list ) min_list = min(input_list, key = lambda i: len(i)) return(min_length, min_list) list1 = [[0], [1, 3], [5, 7], [9, 11], [13, 15, 17]] print("Original list:") print(list1) print("\nList with maximum length of lists:") print(max_length_list(list1)) print("\nList with minimum length of lists:") print(min_length_list(list1))

Write a Python program to convert a given string to camelcase.

from re import sub def camel_case(s): s = sub(r"(_|-)+", " ", s).title().replace(" ", "") return ''.join([s[0].lower(), s[1:]]) print(camel_case('JavaScript')) print(camel_case('Foo-Bar')) print(camel_case('foo_bar')) print(camel_case('--foo.bar')) print(camel_case('Foo-BAR')) print(camel_case('fooBAR')) print(camel_case('foo bar'))

Write a Python program to find common items from two lists.

color1 = "Red", "Green", "Orange", "White" color2 = "Black", "Green", "White", "Pink" print(set(color1) & set(color2))

Write a Python program to create a doubly linked list, append some items and iterate through the list (print forward).

class Node(object): # Doubly linked node def __init__(self, data=None, next=None, prev=None): self.data = data self.next = next self.prev = prev class doubly_linked_list(object): def __init__(self): self.head = None self.tail = None self.count = 0 def append_item(self, data): # Append an item new_item = Node(data, None, None) if self.head is None: self.head = new_item self.tail = self.head else: new_item.prev = self.tail self.tail.next = new_item self.tail = new_item self.count += 1 def print_foward(self): for node in self.iter(): print(node) def iter(self): # Iterate the list current = self.head while current: item_val = current.data current = current.next yield item_val items = doubly_linked_list() items.append_item('PHP') items.append_item('Python') items.append_item('C#') items.append_item('C++') items.append_item('Java') print("Items in the Doubly linked list: ") items.print_foward()

Write a NumPy program to rearrange the dimensions of a given array.

import numpy as np x = np.arange(24).reshape((6,4)) print("Original arrays:") print(x) new_array = np.transpose(x) print("After reverse the dimensions:") print(new_array)

Write a Pandas program to create a series of Timestamps from a DataFrame of integer or string columns. Also create a series of Timestamps using specified columns.

import pandas as pd df = pd.DataFrame({'year': [2018, 2019, 2020], 'month': [2, 3, 4], 'day': [4, 5, 6], 'hour': [2, 3, 4]}) print("Original dataframe:") print(df) result = pd.to_datetime(df) print("\nSeries of Timestamps from the said dataframe:") print(result) print("\nSeries of Timestamps using specified columns:") print(pd.to_datetime(df[['year', 'month', 'day']]))

Write a Python program to create datetime from integers, floats and strings timestamps using arrow module.

import arrow i = arrow.get(1857900545) print("Date from integers: ") print(i) f = arrow.get(1857900545.234323) print("\nDate from floats: ") print(f) s = arrow.get('1857900545') print("\nDate from Strings: ") print(s)

Write a Python program to merge two or more lists into a list of lists, combining elements from each of the input lists based on their positions.

def merge_lists(*args, fill_value = None): max_length = max([len(lst) for lst in args]) result = [] for i in range(max_length): result.append([ args[k][i] if i < len(args[k]) else fill_value for k in range(len(args)) ]) return result print("After merging lists into a list of lists:") print(merge_lists(['a', 'b'], [1, 2], [True, False])) print(merge_lists(['a'], [1, 2], [True, False])) print(merge_lists(['a'], [1, 2], [True, False], fill_value = '_'))

Write a NumPy program to stack arrays in sequence horizontally (column wise).

import numpy as np print("\nOriginal arrays:") x = np.arange(9).reshape(3,3) y = x*3 print("Array-1") print(x) print("Array-2") print(y) new_array = np.hstack((x,y)) print("\nStack arrays in sequence horizontally:") print(new_array)