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Python Articles
Page 625 of 852
Python Program to remove a specific digit from every element of the list
When it is required to remove specific digit from every element of the list, an iteration and ‘set’ operator and ‘str’ methods are used.ExampleBelow is a demonstration of the samemy_list = [123, 565, 1948, 334, 4598] print("The list is :") print(my_list) key = 3 print("The key is :") print(key) my_result = [] for element in my_list: if list(set(str(element)))[0] == str(key) and len(set(str(element))) == 1: my_result.append('') else: my_result.append(int(''.join([element_1 for element_1 in str(element) if int(element_1) != key]))) print("The result ...
Read MorePython Pandas – Display all the column names in a DataFrame
To display only the column names in a DataFrame, use dataframe.columns.Import the required library with an alias −import pandas as pd;Following is the DataFrame −dataFrame = pd.DataFrame( { "Car": ['BMW', 'Audi', 'BMW', 'Lexus', 'Tesla', 'Lexus', 'Mustang'], "Place": ['Delhi', 'Bangalore', 'Hyderabad', 'Chandigarh', 'Pune', 'Mumbai', 'Jaipur'], "Units": [100, 150, 50, 110, 90, 120, 80] } )ExampleDisplay the column names with dataframe.columns. Following is the complete code −import pandas as pd; # create a DataFrame dataFrame = pd.DataFrame( { "Car": ['BMW', 'Audi', 'BMW', 'Lexus', 'Tesla', 'Lexus', 'Mustang'], "Place": ['Delhi', 'Bangalore', 'Hyderabad', ...
Read MorePython Program to check whether all elements in a string list are numeric
When it is required to check wether all elements in a list of strings are numeric, the ‘all’ operator is used.ExampleBelow is a demonstration of the samemy_list = ["434", "823", "98", "74", '9870'] print("The list is :") print(my_list) my_result = all(ele.isdigit() for ele in my_list) if(my_result == True): print("All the elements in the list are numeric") else: print("All the elements in the list are not numeric")OutputThe list is : ['434', '823', '98', '74', '9870'] All the elements in the list are numericExplanationA list of integers is defined and is displayed on ...
Read MorePython Program to Extract Rows of a matrix with Even frequency Elements
When it is required to extract rows of a matrix with even frequency elements, a list comprehension with ‘all’ operator and ‘Counter’ method are used.ExampleBelow is a demonstration of the samefrom collections import Counter my_list = [[41, 25, 25, 62], [41, 41, 41, 41, 22, 22], [65, 57, 65, 57], [11, 24, 36, 48]] print("The list is :") print(my_list) my_result = [sub for sub in my_list if all( value % 2 == 0 for key, value in list(dict(Counter(sub)).items()))] print("The result is :") print(my_result)OutputThe list is : [[41, 25, 25, 62], [41, 41, 41, 41, 22, 22], ...
Read MorePython Program to convert a list into matrix with size of each row increasing by a number
When it is required to convert a list into matrix with the size of every row increasing by a number, the ‘//’ operator and a simple iteration is used.ExampleBelow is a demonstration of the samemy_list = [42, 45, 67, 89, 99, 10, 23, 12, 31, 43, 60, 1, 0] print("The list is :") print(my_list) my_key = 3 print("The value of key is ") print(my_key) my_result = [] for index in range(0, len(my_list) // my_key): my_result.append(my_list[0: (index + 1) * my_key]) print("The resultant matrix is :") print(my_result)OutputThe list is : [42, 45, 67, ...
Read MorePython program to sort tuples by frequency of their absolute difference
When it is required to sort tuples by frequency of their absolute difference, the lambda function, the ‘abs’ method and the ‘sorted’ method are used.ExampleBelow is a demonstration of the samemy_list = [(11, 26), (21, 33), (90, 11), (26, 21), (32, 18), (25, 37)] print("The list is :") print(my_list) my_diff_list = [abs(x - y) for x, y in my_list] my_result = sorted(my_list, key = lambda sub: my_diff_list.count(abs(sub[0] - sub[1]))) print("The resultant list is :") print(my_result)OutputThe list is : [(11, 26), (21, 33), (90, 11), (26, 21), (32, 18), (25, 37)] The resultant list is : [(11, ...
Read MorePython Program to Remove First Diagonal Elements from a Square Matrix
When it is required to remove the first diagonal elements from a square matrix, the ‘enumerate’ and list comprehension is used.ExampleBelow is a demonstration of the samemy_list = [[45, 67, 85, 42, 11], [78, 99, 10, 13, 0], [91, 23, 23, 64, 23], [91, 11, 22, 14, 35]] print("The list is :") print(my_list) my_result = [] for index, element in enumerate(my_list): my_result.append([ele for index_1, ele in enumerate(element) if index_1 != index]) print("The resultant matrix is :") print(my_result)OutputThe list is : [[45, 67, 85, 42, 11], [78, 99, 10, 13, 0], [91, 23, 23, ...
Read MorePython Program to Extract Strings with at least given number of characters from other list
When it is required to extract strings with atleast a given number of characters from the other list, a list comprehension is used.ExampleBelow is a demonstration of the samemy_list = ["Python", "is", "fun", "to", "learn"] print("The list is :") print(my_list) my_char_list = ['e', 't', 's', 'm', 'n'] my_key = 2 print("The value of key is ") print(my_key) my_result = [element for element in my_list if sum(ch in my_char_list for ch in element) >= my_key] print("The resultant list is :") print(my_result)OutputThe list is : ['Python', 'is', 'fun', 'to', 'learn'] The value of key is 2 The ...
Read MorePython program to randomly create N Lists of K size
When it is required to create N lists randomly that are K in size, a method is defined that shuffles the values and yields the output.ExampleBelow is a demonstration of the samefrom random import shuffle def gen_random_list(my_val, K): while True: shuffle(my_val) yield my_val[:K] my_list = [12, 45, 76, 32, 45, 88, 99, 0, 1] print("The list is ") print(my_list) K, N = 4, 5 print("The value of K is ") print(K) print("The value of N is ") print(N) my_result = [] ...
Read MorePython - Count distinct in Pandas Aggregation with Numpy
To count distinct, use nunique in Pandas. We will groupby a column and find sun as well using Numpy sum().At first, import the required libraries −import pandas as pd import numpy as npCreate a DataFrame with 3 columns. The columns have duplicate values −dataFrame = pd.DataFrame( { "Car": ['BMW', 'Audi', 'BMW', 'Lexus', 'Lexus'], "Place": ['Delhi', 'Bangalore', 'Delhi', 'Chandigarh', 'Chandigarh'], "Units": [100, 150, 50, 110, 90] } )Count distinct in aggregation agg() with nunique. Calculating the sum for counting, we are using numpy sum() −dataFrame = dataFrame.groupby("Car").agg({"Units": np.sum, "Place": pd.Series.nunique})ExampleFollowing is the code −import ...
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