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ROC − Receiver operating characteristics (ROC) curve.Using metrics.plot_roc_curve(clf, X_test, y_test) method, we can draw the ROC curve.StepsGenerate a random n-class classification problem. This initially creates clusters of points normally distributed (std=1) about vertices of an ``n_informative``-dimensional hypercube with sides of length ``2*class_sep`` and assigns an equal number of clusters to each class.It introduces interdependence between these features and adds various types of further noise to the data. Use the make_classification() method.Split arrays or matrices into random trains, using train_test_split() method.Fit the SVM model according to the given training data, using fit() method.Plot Receiver operating characteristic (ROC) curve, using plot_roc_curve() method.To ... Read More
Using plt.subplots(1, 1) method, we can create fig and axis. We can use fig.colorbar to make the color bar at the midpoint of the figure.StepsUsing mgrid() method, `nd_grid` instance which returns an open multi-dimensional "meshgrid".Create Z1, Z2 and Z data.Create fig and ax variables using subplots method, where default nrows and ncols are 1, using subplots() method.Create a colorbar for a ScalarMappable instance, *mappable*, using colorbar() method.Using plt.show(), we can show the figure.Exampleimport numpy as np import matplotlib.pyplot as plt import matplotlib.colors as colors N = 100 X, Y = np.mgrid[-3:3:complex(0, N), -2:2:complex(0, N)] Z1 = np.exp(-(X)**2 - ... Read More
In this program, we will print today's, yesterday's and tomorrow's dates using the numpy library.AlgorithmStep 1: Import the numpy library. Step 2: find today's date using the datetime64() function. Step 3: find yesterday's date by subtracting the output of timedelta64() function from the output of datetime64() function. Step 4: Find yesterday's date by adding the output of timedelta64() function from the output of datetime64() function.Example Codeimport numpy as np todays_date = np.datetime64('today', 'D') print("Today's Date: ", todays_date) yesterdays_date = np.datetime64('today', 'D') - np.timedelta64(1, 'D') print("Yesterday's Date: ", yesterdays_date) tomorrows_date = np.datetime64('today', 'D') + np.timedelta64(1, 'D') print("Tomorrow's Date: ... Read More
To convert negative values in a matrix to 0, we can use pmax function. For example, if we have a matrix called M that contains some negative and some positive and zero values then the negative values in M can be converted to 0 by using the command pmax(M,0).ExampleConsider the below data frame − Live DemoM1
In this program, we will draw different shapes using the Turtle library in Python. Turtle is a python feature like a drawing board, which lets you command a turtle to draw all over it. The different shapes that we are going to draw are square, rectangle, circle and a hexagon.AlgorithmStep 1: Take lengths of side for different shapes as input.Step 2: Use different turtle methods like forward() and left() for drawing different shapes.Example Codeimport turtle t = turtle.Turtle() #SQUARE side = int(input("Length of side: ")) for i in range(4): t.forward(side) t.left(90) #RECTANGLE side_a = int(input("Length of ... Read More
We can use matplotlib.rcParams['backend'] to override the backend value.StepsUsing get_backend() method, return the name of the current backend, i.e., default name.Now override the backend name.Using get_backend() method, return the name of the current backend, i.e., updated name.Exampleimport matplotlib print("Before, Backend used by matplotlib is: ", matplotlib.get_backend()) matplotlib.rcParams['backend'] = 'TkAgg' print("After, Backend used by matplotlib is: ", matplotlib.get_backend())OutputBefore, Backend used by matplotlib is: GTK3Agg After, Backend used by matplotlib is: TkAgg
We can create a scatter plot using the scatter() method and we can set the color for every data point.StepsCreate random values (for x and y) in a given shape, using np.random.rand() method.Create a scatter plot of *y* vs. *x* with varying marker size and/or color, using the scatter method where color range would be in the range of (0, 1000).Show the figure using plt.show().Exampleimport matplotlib.pyplot as plt import numpy as np x = np.random.rand(1000) y = np.random.rand(1000) plt.scatter(x, y, c=[i for i in range(1000)]) plt.show()OutputRead More
Using pylab.gcf(), we can create a fig variable and can set the fig.canvas.set_window_title('Setting up window title.') window title.StepsUsing gcf() method, get the current figure. If no current figure exists, a new one is created using `~.pyplot.figure()`.Set the title text of the window containing the figure, using set_window_title() method.. Note that this has no effect if there is no window (e.g., a PS backend).ExamplePlease use Ipython and follow the steps given below -In [1]: from matplotlib import pylab In [2]: fig = pylab.gcf() In [3]: fig.canvas.set_window_title('Setting up window title.')OutputRead More
In this program, we will declare two Pandas series and compare their elements. Before we solve the problem, we need to import the Pandas library into our local IDE. This can be done by installing Pandas on our local machine. The command for installing Pandas is −pip install pandasInputSeries1 = [2,4,6,8,10]Series2 = [1,3,5,7,9]AlgorithmStep 1: Define two Pandas series using the Series() function of Pandas library.Step 2: Compare the series using greater than, less than, and equal-to operators.Example Codeimport pandas as pd series1 = pd.Series([2,4,6,8,10]) series2 = pd.Series([1,3,5,7,9]) print("Greater Than: ",series1>series2) print("Less Than: ",series1
To minus one column from another in an R matrix, we first need to read the matrix as a data frame using as.data.frame then find minus the columns using minus sign and accessing the column of the data frame. To understand how it can be done look at the steps in below examples.ExampleConsider the below data frame − Live DemoM1