Found 1034 Articles for Matplotlib

Using Pandas, we can create a data frame and create a figure and axis. After that, we can use the scatter method to draw points.StepsCreate lists of students, marks obtained by them, and color codings for each score.Make a data frame using Panda’s DataFrame, with step 1 data.Create fig and ax variables using subplots method, where default nrows and ncols are 1.Set the X-axis label using plt.xlabel() method.Set the Y-axis label using plt.ylabel() method.A scatter plot of *y* vs. *x* with varying marker size and/or color.To show the figure, use plt.show() method.Examplefrom matplotlib import pyplot as plt import pandas as ... Read More

We can first activate the figure using plt.ion() method. Then, we can update the plot with different sets of values.StepsCreate fig and ax variables using subplots method, where default nrows and ncols are 1.Draw a line, using plot() method.Set the color of line, i.e., orange.Activate the interaction, using plt.ion() method.To make the plots interactive, change the line coordinates.ExampleIn [1]: %matplotlib auto Using matplotlib backend: GTK3Agg In [2]: import matplotlib.pyplot as plt # Diagram will get popped up. Let’s update the diagram. In [3]: fig, ax = plt.subplots() # Drawing a line In [4]: ax.plot(range(5)) In ... 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

In this program, we will plot two lines using the matplot library. Before starting to code, we need to first import the matplotlib library using the following command −Import matplotlib.pyplot as pltPyplot is a collection of command style functions that make matplotlib work like MATLAB.AlgorithmStep 1: Import matplotlib.pyplot Step 2: Define line1 and line2 points. Step 3: Plot the lines using the plot() function in pyplot. Step 4: Define the title, X-axis, Y-axis. Step 5: Display the plots using the show() function.Example Codeimport matplotlib.pyplot as plt line1_x = [10, 20, 30] line1_y = [20, 40, 10] line2_x = ... Read 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

Using plt.xticks, we can change the X-axis scale.StepsUsing plt.plot() method, we can create a line with two lists that are passed in its argument.Add text to the axes. Add the text *s* to the axes at location *x*, *y* in data coordinates, using plt.text() method, where the font size can be customized by changing the font-size value.Using xticks method, get or set the current tick locations and labels of the X-axis.To show the figure, use plt.show() method.Exampleimport matplotlib.pyplot as plt plt.plot([1, 2, 4], [1, 2, 4]) plt.text(2, 3, "y=x", color='red', fontsize=20) plt.xticks([1, 2, 3, 4, 5])   ... Read More

Using plt.text() method, we can increase the font size.StepsUsing plt.plot() method, we can create a line with two lists that are passed in its argument.Add text to the axes. Add the text *s* to the axes at location *x*, *y* in data coordinates, using plt.text() method. Font size can be customized by changing the font-size value.To show the figure, use plt.show() method.Exampleimport matplotlib.pyplot as plt plt.plot([1, 2, 4], [1, 2, 4]) plt.text(2, 3, "y=x", color='red', fontsize=20) # Increase fontsize by increasing value. plt.show()Output

We can use a user-defined method, autolabel, to annotate the axis value. Before that, we can initialize the fig and ax using plt.subplots() method.StepsCreate lists, labels, men_means, and women_means with different data elements.Return evenly spaced values within a given interval, using numpy.arrange() method.Set the width variable i.e., width=0.35.Create fig and ax variables using subplots method, where default nrows and ncols are 1.The bars are positioned at *x* with the given *align*\ment. Their dimensions are given by *height* and *width*. The vertical baseline is *bottom* (default 0), so create rect1 and rect2 using plt.bar() method.Set the Y-axis label using plt.ylabel() method.Set ... Read More

In this program, we can create a data frame and can plot a bar using df.plot.bar(x='lab', y='value', color='#5fba34') plot.StepsUsing Panda’s dataframe, we can create a data frame with the given dictionary, where the keys are lab and value, values of these keys are lists, respectively.Using Pandas plot.bar() method, we can create a vertical bar plot. A bar plot is a plot that presents categorical data with rectangular bars with lengths proportional to the values that they represent.To show the figure, use the plt.show() method.Exampleimport pandas as pd from matplotlib import pyplot as plt df = pd.DataFrame({'lab': ['A', 'B', 'C'], ... Read More