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Articles by Rishikesh Kumar Rishi
Page 15 of 102
How to avoid line color repetition in matplotlib.pyplot?
To avoid line color repetition in matplotlib.pyplot we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create x and y data points using numpy.Plot the x and y data points using plot() method.In the plot() method, use a unique hexadecimal value for the color attribure, for example, color="#980ab5" to set the graph in a unique color. You can also specify a particular color of your choice, for example, color="green".To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] ...
Read MoreHow to plot multiple horizontal bars in one chart with matplotlib?
To plot multiple horizontal bars in one chart with matplotlib, we can take the following steps −StepsImport the libraries pandas, matplotlib, and numpy.Set the figure size and adjust the padding between and around the subplots.Create an array for horizontal bar's position.Initialize a variable width for bar's width.Create a horizontal bar plot.Set Y-axis ticks and tick labels with some limit.Place a legend on the plot at the upper right location.To display the figure, use show() method.Exampleimport pandas import matplotlib.pyplot as plt import numpy as np # Set the figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # Array ...
Read MoreHow to set the value of the axis multiplier in matplotlib?
To set the value of the axis multiplier in matplotlib, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create x data points using numpy.Plot x and x2 using plot() method.Get the current axis of the figure.Initialize a variable multiplier, i.e., a value of the axis multiplier.Set a tick on each integer multiple of a base within the view interval.Set the locator of the major ticker.To display the figure, use show() method.Example# Import matplotlib and numpy from matplotlib import pyplot as plt import numpy as np # Set the figure ...
Read MoreIn Matplotlib, show the percentage or proportional data where each slice of pie represents a category
In this article, we can create a pie chart to show our daily activities, i.e., sleeping, eating, working, and playing. Using plt.pie() method, we can create a pie chart with the given different data sets for different activities.StepsCreate a list of days, i.e., [1, 2, 3, 4, 5]. Similarly, make lists for sleeping, eating, playing, and working. There is an activities list that keeps “sleeping”, “eating”, “working” and “playing”.Make a list of colors.Use plt.pie() method to draw the pie chart, where slices, activities, colors as cols, etc. are passed.Set a title for the axes, i.e., “Pie Chart”.To show the figure ...
Read MoreWhat is the equivalent of Matlab's surf(x,y,z,c) in Matplotlib?
Let's take an example to see how to get the same effect as MatLab's surf(x, y, z, c) in Matplotlib. steps −Set the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Create r, u, v, x, y and z data points using Numpy.Create a surface plot.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax = fig.add_subplot(projection='3d') r = 0.05 u, v ...
Read MoreHow to curve text in a polar plot in matplotlib?
To curve text in a polar plot in matplotlib we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Plot the line with some degree, color='green' and linewidth=2.Create x and y data points, with some curve and plot them using plot() method.To display the figure, use Show() method.Examplefrom matplotlib import pyplot as plt from scipy.interpolate import interp1d import numpy as np plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() ax ...
Read MoreHow to put xtick labels in a box matplotlib?
To put xtick labels in a box, we can take the following stepsStepsCreate a new figure or activate an existing figure.Get the current axis of the figure.Set the left and bottom position of the axes.Set the position of the spines, i.e., bottom and left.To put xtick labels in a box, iterate the ticklabels and use set_bbox() method.To display the figure, use Show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True plt.figure() ax = plt.gca() ax.xaxis.set_ticks_position('bottom') ax.yaxis.set_ticks_position('left') ax.spines['bottom'].set_position(('data', 0)) ax.spines['left'].set_position(('data', 0)) for label in ax.get_xticklabels(): label.set_fontsize(12) label.set_bbox(dict(facecolor='red', edgecolor='black', alpha=0.7)) ...
Read MoreHow to plot a time as an index value in a Pandas dataframe in Matplotlib?
To plot a time as an index value in a Pandas dataframe in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create a Pandas dataframe with two columns, time and speed.Set the DataFrame index using existing columns.To display the figure, use Show() method.Examplefrom matplotlib import pyplot as plt import pandas as pd import numpy as np # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Pandas dataframe df = pd.DataFrame(dict(time=list(pd.date_range("2021-01-01 12:00:00", periods=10)), speed=np.linspace(1, 10, 10))) # Set the dataframe index df.set_index('time').plot() # ...
Read MoreHow to remove the axis tick marks on a Seaborn heatmap?
To remove the axis tick marks on a Seaborn heatmap, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create random data points with 4×4 dimension.Plot the rectangular data as a color-encoded matrix.Use tick_params() for changing the appearance of ticks and tick labels. Use left=false and bottom=false to remove the tick marks.To display the figure, use Show() method.Exampleimport numpy as np import seaborn as sns from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True data = np.random.rand(4, 4) ax = sns.heatmap(data, vmax=1) ax.tick_params(left=False, bottom=False) ...
Read MoreMake logically shading region for a curve in matplotlib
To make logically shading region for a curve in matplotlib, we can take the following stepsStepsSet the figure size and adjust the padding between and around the subplots.Create t, s1 and s2 data points using numpy.Create a figure and a set of subplots.Plot t and s1 data points; add a horizontal line across the axis.Create a collection of horizontal bars spanning *yrange* with a sequence of xranges.Add a '~.Collection' to the axes' collections; return the collection.To display the figure, use Show() method.Exampleimport numpy as np import matplotlib.pyplot as plt import matplotlib.collections as collections plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True ...
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