Article Categories
- All Categories
-
Data Structure
-
Networking
-
RDBMS
-
Operating System
-
Java
-
MS Excel
-
iOS
-
HTML
-
CSS
-
Android
-
Python
-
C Programming
-
C++
-
C#
-
MongoDB
-
MySQL
-
Javascript
-
PHP
-
Economics & Finance
Matplotlib Articles
Page 87 of 91
How to generate random colors in Matplotlib?
To make a custom color, we can create a hexadecimal string. From it, we can make different sets of color representation and can pass into the scatter method to get the desired output.StepsTake an input from the user for the number of colors, i.e., number_of_colors = 20.Use Hexadecimal alphabets to get a color.Create a color from (step 2) by choosing a random character from step 2 data.Plot scatter points for step 1 input data, with step 3 colors.To show the figure, use plt.show() method.Exampleimport matplotlib.pyplot as plt import random number_of_colors = int(input("Please enter number of colors: ")) hexadecimal_alphabets ...
Read MoreHow to give a Pandas/Matplotlib bar graph custom colors?
To make a custom color, we can create a hexadecimal string. From it, we can make different sets of color representation and can pass them into the scatter method to get the desired output.Using the set_color method, we could set the color of the bar.StepsTake user input for the number of bars.Add bar using plt.bar() method.Create colors from hexadecimal alphabets by choosing random characters.Set the color for every bar, using set_color() method.To show the figure we can use plt.show() method.Examplefrom matplotlib import pyplot as plt import random bar_count = int(input("Enter number of bars: ")) bars = plt.bar([i for ...
Read MoreHow to change backends in Matplotlib?
We can override the backend value using atplotlib.rcParams['backend'] variable.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 Enter number of bars: 5
Read MoreRow and column headers in Matplotlib's subplots
Using the subplot method, we can configure the number of rows and columns. nrows*nclos will create number positions to draw a diagram.StepsNumber of rows = 2, Number of columns = 1, so total locations are: 2*1 = 2.Add a subplot to the current figure, nrow = 2, ncols = 1, index = 1.Add a subplot to the current figure, nrow = 2, ncols = 1, index = 2.Using plt.show(), we can show the figure.Examplefrom matplotlib import pyplot as plt row_count = 2 col_count = 1 index1 = 1 # no. of subplots are: row*col, index is the position ...
Read MoreWhat is the currently correct way to dynamically update plots in Jupyter/iPython?
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 MoreDefining the midpoint of a colormap in Matplotlib
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 MoreChange figure window title in pylab(Python)
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.')Output
Read MoreChange x axes scale in matplotlib
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 MorePython matplotlib multiple bars
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 MoreGetting vertical gridlines to appear in line plot in matplotlib
Using plt.grid(axis="x") method, we can plot vertical gridlines.StepsMake a list of numbers.Set the X-axis label using plt.xlabel() method.Set the Y-axis label using plt.ylabel() method.Toggle the gridlines, and optionally set the properties of the lines, using plt.grid() method.To show the figure, use the plt.show() method, where the argument axis can be “x”, “y” or “both”.Examplefrom matplotlib import pyplot as plt plt.plot([0, 5], [0, 5]) plt.ylabel("Y-axis ") plt.xlabel("X-axis ") plt.grid(axis="x") plt.show()Output
Read More