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Articles by Prasad Naik
Page 3 of 4
Comparing two Pandas series and printing the the difference
In this program, we will compare two Pandas series and will print the differences in the series. By difference, we mean that the index positions at which the elements did not match.AlgorithmStep 1: Define two Pandas series, s1 and s2. Step 2: Compare the series using compare() function in the Pandas series. Step 3: Print their difference.Example Codeimport pandas as pd s1 = pd.Series([10, 20, 30, 40, 50, 60]) s2 = pd.Series([10, 30, 30, 40, 55, 60]) print("S1:", s1) print("S2:", s2) difference = s1.compare(s2) print("Difference between the series: ", difference)OutputS1: 0 10 1 20 2 ...
Read MorePrint the standard deviation of Pandas series
In this program, we will find the standard deviation of a Pandas series. Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance.AlgorithmStep 1: Define a Pandas series Step 2: Calculate the standard deviation of the series using the std() function in the pandas library. Step 3: Print the standard deviation.Example Codeimport pandas as pd series = pd.Series([10,20,30,40,50]) print("Series: ", series) series_std = series.std() print("Standard Deviation of the series: ",series.std())OutputSeries: 0 10 1 20 2 30 3 40 4 50 dtype: int64 Standard Deviation of the series: 15.811388300841896
Read MorePrint the mean of a Pandas series
mean() function in the Pandas library can be used to find the mean of a series.AlgorithmStep 1: Define a Pandas series. Step 2: Use the mean() function to calculate the mean. Step 3: Print the mean.Example Codeimport pandas as pd series = pd.Series([10,20,30,40,50]) print("Pandas Series: ", series) series_mean = series.mean() print("Mean of the Pandas series:", series_mean)OutputPandas Series: 0 10 1 20 2 30 3 40 4 50 dtype: int64 Mean of the Pandas series: 30.0
Read MoreHow to append elements to a Pandas series?
In this program, we will append elements to a Pandas series. We will use the append() function for this task. Please note that we can only append a series or list/tuple of series to the existing series.AlgorithmStep1: Define a Pandas series, s1. Step 2: Define another series, s2. Step 3: Append s2 to s1. Step 4: Print the final appended series.Example Codeimport pandas as pd s1 = pd.Series([10, 20, 30, 40, 50]) s2 = pd.Series([11, 22, 33, 44, 55]) print("S1:", s1) print("S2:", s2) appended_series = s1.append(s2) print("Final Series after appending:", appended_series)OutputS1: 0 10 1 20 ...
Read MoreHow to sort a Pandas Series?
In this problem we have to sort a Pandas series. We will define an unsorted pandas series and will sort it using the sort_values() function in the Pandas library.AlgorithmStep 1: Define Pandas series. Step 2: Sort the series using sort_values() function. Step 3: Print the sorted series.Example Codeimport pandas as pd panda_series = pd.Series([18, 15, 66, 92, 55, 989]) print("Unsorted Pandas Series: ", panda_series) panda_series_sorted = panda_series.sort_values(ascending = True) print("Sorted Pandas Series: ", panda_series_sorted)OutputUnsorted Pandas Series: 0 18 1 15 2 66 3 92 4 55 5 ...
Read MoreHow to print array elements within a given range using Numpy?
In this program, we have to print elements of a numpy array in a given range. The different numpy functions used are numpy.where() and numpy.logical_and().AlgorithmStep 1: Define a numpy array. Step 2: Use np.where() and np.logical_and() to find the numbers within the given range. Step 3: Print the result.Example Codeimport numpy as np arr = np.array([1,3,5,7,10,2,4,6,8,10,36]) print("Original Array:",arr) result = np.where(np.logical_and(arr>=4, arr
Read MoreHow to add a vector to a given Numpy array?
In this problem, we have to add a vector/array to a numpy array. We will define the numpy array as well as the vector and add them to get the result arrayAlgorithmStep 1: Define a numpy array. Step 2: Define a vector. Step 3: Create a result array same as the original array. Step 4: Add vector to each row of the original array. Step 5: Print the result array.Example Codeimport numpy as np original_array = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]]) print("Original Array: ", original_array) vector = np.array([1, 1, 0]) print("Vector: ...
Read MoreHow to find the sum of rows and columns of a given matrix using Numpy?
In this problem, we will find the sum of all the rows and all the columns separately. We will use the sum() function for obtaining the sum.AlgorithmStep 1: Import numpy. Step 2: Create a numpy matrix of mxn dimension. Step 3: Obtain the sum of all the rows. Step 4: Obtain the sum of all the columns.Example Codeimport numpy as np a = np.matrix('10 20; 30 40') print("Our matrix: ", a) sum_of_rows = np.sum(a, axis = 0) print("Sum of all the rows: ", sum_of_rows) sum_of_cols = np.sum(a, axis = 1) print("Sum of all the columns: ", sum_of_cols)OutputOur ...
Read MoreHow to create an identity matrix using Numpy?
In this program, we will print an identity matrix of size nxn where n will be taken as an input from the user. We shall use the identity() function in the numpy library which takes in the dimension and the data type of the elements as parametersAlgorithmStep 1: Import numpy. Step 2: Take dimensions as input from the user. Step 3: Print the identity matrix using numpy.identity() function.Example Codeimport numpy as np dimension = int(input("Enter the dimension of identitiy matrix: ")) identity_matrix = np.identity(dimension, dtype="int") print(identity_matrix)OutputEnter the dimension of identitiy matrix: 5 [[1 0 0 0 0] [0 1 0 0 0] [0 0 1 0 0] [0 0 0 1 0] [0 0 0 0 1]]
Read MoreFinding the number of rows and columns in a given matrix using Numpy
We will first create a numpy matrix and then find out the number of rows and columns in that matrixAlgorithmStep 1: Create a numpy matrix of random numbers. Step 2: Find the rows and columns of the matrix using numpy.shape function. Step 3: Print the number of rows and columns.Example Codeimport numpy as np matrix = np.random.rand(2,3) print(matrix) print("Total number of rows and columns in the given matrix are: ", matrix.shape)Output[[0.23226052 0.89690884 0.19813164] [0.85170808 0.97725669 0.72454096]] Total number of rows and columns in the given matrix are: (2, 3)
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