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The dictionary is one of the famous datatypes of Python that consist of keys with value pairs. The strings list is the set of elements that are represented either in a single or double quotation. In Python, we have some built-in functions such as keys(), set(), intersection, and append() will be used to find the dictionary keys present in strings List. Let’s take an example of this. There are two available sets:- The given dictionary, {'T': 1, 'M': 2, 'E': 3, 'C': 4} The given list, [T, A, B, P, E, L] Therefore, the final result becomes [T, E]. ... Read More

The tuple is a popular datatype of Python that represents the collection of objects or elements separated by commas. The frequency of data type defines the total number of counts of a specific variable type. Python has four primitive variable types: integer, float, boolean, and string. In Python, we have some built-in functions such as type(), isinstance(), filter(), lambda, len(), and list() will be used to Find the frequency of a given Datatype in a Python tuple. Syntax The following syntax is used in the examples- type() The type() is an in-built function in Python that returns the type ... Read More

The stream of strings is a sequential flow of given data where an individual element of the stream represents a string. The stream allows a large process of string data In C++, we have some STL(Standard template library) based functions such as count() and insert() to Check duplicate in a stream of strings. Using Standard Template Library The program uses C++ STL to set the header file unordered representing the unique key element and helps to solve the duplicates in a stream of strings. Syntax The following syntax is used in the examples- static unordered_set unq_string; The ... Read More

The suffix of keys is a group of letters that is mentioned at the end of the word. In this problem statement, we need to create the specific variable that set the suffix key to filter the result by using some specific conditions. In Python, we have some built-in functions such as endswith(), filter(), lambda, append(), and, items() that will be used to Find Keys with specific suffix in Dictionary. Let’s take an example of this. The given dictionary, my_dict = {'compiler': 100, 'interpreter': 200, 'cooperative': 300, 'cloudbox': 400, 'database': 500} The suffix key is set to er, ... Read More

The tuple is ordered or a finite sequence to collect the data. It can be represented by using parenthesis i.e. (). A byte integer is a simple number without having decimal or fractional values. In Python, we have some built-in functions such as from_bytes(), bytes(), unpack(), and, enumerate() will be used to Interconvert Tuple to Byte Integer. Syntax The following syntax is used in the examples from_bytes() The from_bytes() is an in-built function in Python that accepts two specific parameters bytes()- The bytes() is also a built-in function that defines the immutable series of integers. byteorder- The byteorder ... Read More

The Index match element Product refers to two different lists where it contains the elements and set to respective variable. If common matches are found, then it filters the element by multiplication. To solve this problem statement, Python has some built-in functions such as range(), len(), zip(), prod(), reduce(), and, lambda(). Let’s take an example of this. The given input lists: list_1 = [10, 20, 30, 40] list_2 = [10, 29, 30, 10] So, the common matches found in indexes 0 and 2 and its product become 10*30 = 300. Syntax The following syntax is used in the examples ... Read More

The atmost K element is set to a specific value in the given list to filter those indices whose elements are greater than the K value. In Python, we have some built-in functions such as enumerate(), range(), len(), where(), map(), range(), and, filter() that will be used to solve the Indices of atmost K elements in list. Let’s take an example of this. The given list, [10, 8, 13, 29, 7, 40, 91] and the K value set to 13. Now, it will check how many elements are less than or equal to 12 and filter those indices which are ... Read More

The frequency of elements consists of two different lists where one list defines the unique element and the other list defines the number of repetitions of the same element w.r.t to the first list. Then use some conditions and operations in the dictionary to set each element of the first list represented by a key whereas the value pair will be represented by counting the total number of repetitions of key element in the second list. In Python, we have some built-in functions such as Counter(), count(), defaultdict(), and, unique() will be used to solve the Frequency of elements from ... Read More

The K difference is set to any value that will be used to set the difference between two numbers. The consecutive element is those elements that follow the sequential order. In Python, we have some built-in functions such as range(), len(), abs(), append(), and, sort() will be used to solve the K difference Consecutive element. Let’s take an example of this. The given list, [5, 6, 3, 2, 4, 3, 4] The K value set to 1 means each consecutive elements follow the differences of 5. Then the final result becomes, [True, False, True, False, True, True] Explanation: The outcome ... Read More

Statistics provides us with powerful tools to analyze and understand data. One of the fundamental concepts in statistics is the 68-95-99.7 rule, also known as the empirical rule or the three-sigma rule. This rule allows us to make important inferences about the distribution of data based on its standard deviation. In this blog post, we will explore the 68-95-99.7 rule and demonstrate how to apply it using Python. Overview of the 68-95-99.7 Rule The 68-95-99.7 rule provides a way to estimate the percentage of data that falls within a certain number of standard deviations from the mean in a normal ... Read More