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Data Visualization Articles
Page 12 of 68
How to make a polygon radar (spider) chart in Python Matplotlib?
To make a polygon radar (spider) chart in Python, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create a Pandas dataframe with sports and values columns.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Based on data frame values, get the theta value.Get the values list of the data frame.Make a bar plot with theta and values data points.Fill the area between polygon.To display the figure, use show() method.Exampleimport pandas as pd import matplotlib.pyplot as plt import numpy as np ...
Read MoreHow to specify different colors for different bars in a Python matplotlib histogram?
To specify different colors for different bars in a matplotlib histogram, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Plot a histogram with random data with 100 sample data.Iterate in the range of number of bins and set random facecolor for each bar.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt import random import string # Set the figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # Figure and set of subplots fig, ax = ...
Read MoreHow do I fill a region with only hatch (no background colour) in matplotlib 2.0?
To fill a region with only hatch (no background color) in matplotlib, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Initialize a variable n to store the number of sample data.Create a figure and a set of subplots.Plot the x and y data points.Fill the area between x and y with circle hatches, edgecolor="blue".To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # Number of sample data n = 256 ...
Read MoreHow to set a line color to orange, and specify line markers in Matplotlib?
To set a line color to orange, and specify line markers in matplotlib, 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 with the attributes color='orange' and marker='*'.To display the figure, use show() method.Exampleimport 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 # x and y data points x = np.linspace(-5, 5, 100) y = np.sin(x) # Plot the data points with color ...
Read MoreHow to deal with NaN values while plotting a boxplot using Python Matplotlib?
To deal with NaN value while plotting a boxplot using Python, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Initialize a variable N for data samples and for range.Next create the random spread, center's data, flier high and low, get the concatenated data, and the filtered data.Create a box plot using boxplot() method.To display the figure, use show() method.Exampleimport 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 # Data samples N = 10 # Random spread ...
Read MoreHow to plot a smooth line with matplotlib?
To plot a smooth line with matplotlib, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create a list of data points, x and y.Plot the x and y data points.Create x_new and bspline data points for smooth line.Get y_new data points. Compute the (coefficients of) interpolating B-spline.Plot x_new and y_new data points using plot() method.To display the figure, use show() method.Exampleimport numpy as np from matplotlib import pyplot as plt from scipy import interpolate # Set the figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # x ...
Read MoreHow 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 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 ...
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