Found 735 Articles for Data Visualization

How to fill an area within a polygon in Python using matplotlib?

Rishikesh Kumar Rishi
Updated on 02-Feb-2022 11:47:09
To fill an area within a polygon in Python using matplotlib, 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.Get an instance of a polygon.Get the generic collection of patches with iterable polygons.Add a 'collection' to the axes' collections; return the collection.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt from matplotlib.collections import PatchCollection from matplotlib.patches import Polygon import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig, ax = plt.subplots(1) polygon = Polygon(np.random.rand(6, 2), closed=True, alpha=1) ... Read More

How to get data labels on a Seaborn pointplot?

Rishikesh Kumar Rishi
Updated on 02-Feb-2022 11:37:50
To get data labels on a Seaborn pointplot, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create a dataframe, df, of two-dimensional, size-mutable, potentially heterogeneous tabular data.Create a pointplot.Get the axes patches and label; annotate with respective labels.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt import pandas as pd import seaborn as sns plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True df = pd.DataFrame({'a': [1, 3, 1, 2, 3, 1]}) ax = sns.pointplot(df["a"],    order=df["a"].value_counts().index) for p, label in zip(ax.patches, df["a"].value_counts().index):    ax.annotate(label, ... Read More

How to draw a precision-recall curve with interpolation in Python Matplotlib?

Rishikesh Kumar Rishi
Updated on 02-Feb-2022 11:33:00
To draw a precision-recall curve with interpolation in Python, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create r, p and duplicate recall, i data points using numpy.Create a figure and a set of subplots.Plot the recall matrix in the range of r.shape.Plot the r and dup_r data points using plot() method.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True r = np.linspace(0.0, 1.0, num=10) p = np.random.rand(10) * (1. - r) dup_p = p.copy() i ... Read More

How to plot additional points on the top of a scatter plot in Matplotlib?

Rishikesh Kumar Rishi
Updated on 02-Feb-2022 11:29:47
To plot additional points on the top of a scatter plot in matplotlib, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Make a list of x and y data points.Create a scatter plot with x and y data points.Plot the additional points with marker='*'To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True # List of data points x = [1, 2, 6, 4] y = [1, 5, 2, 3] # Scatter plot ... Read More

Transparent error bars without affecting the markers in Matplotlib

Rishikesh Kumar Rishi
Updated on 02-Feb-2022 11:26:04
To make transparent error bars without affecting markers in matplotlib, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Make lists x, y and z for data.Initialize a variable error_bar_width=5Plot y versus x as lines and/or markers with attached errorbars.Set the alpha value of bars and caps.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = [1, 3, 5, 7] y = [1, 3, 5, 7] z = [4, 5, 1, 4] error_bar_width = 5 markers, ... Read More

How to set legend marker size and alpha in Matplotlib?

Rishikesh Kumar Rishi
Updated on 02-Feb-2022 11:21:30
To set legend marker size and alpha 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.Plot the x and y data points with marker="*".Place a legend on the figure.Set the marker size and alpha value of the marker.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 N = 10 x = np.random.rand(N) y = np.random.rand(N) line, = plt.plot(x, y, marker='*', markersize=20, markeredgecolor='black', ... Read More

Showing points coordinate in a plot in Python Matplotlib

Rishikesh Kumar Rishi
Updated on 02-Feb-2022 11:17:43
To show points coordinate in a plot in Python, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Initilize a variable N and create x and y data points using numpy.Zip the x and y data points; iterate them and place coordinates.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 N = 5 x = np.random.rand(N) y = np.random.rand(N) plt.plot(x, y, 'r*') for xy in zip(x, y):    plt.annotate('(%.2f, %.2f)' % xy, xy=xy) ... Read More

How to unset 'sharex' or 'sharey' from two axes in Matplotlib?

Rishikesh Kumar Rishi
Updated on 02-Feb-2022 11:13:03
To inset sharex and sharey from two axes in matplotlib, we can use 'none', i.e., False or 'none'. Each subplot X- or Y-axis will be independent.StepsSet the figure size and adjust the padding between and around the subplots.Initialize two variables rows and cols.Create a figure and a set of subplots.Iterate the axes where rows=2 and cols=4.Plot the random data on the axis.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 rows = 2 cols = 4 fig, axes = plt.subplots(rows, cols, sharex='none', sharey='none', squeeze=False) ... Read More

How to obtain 3D colored surface via Python?

Rishikesh Kumar Rishi
Updated on 02-Feb-2022 10:55:15
To obtain 3D colored surface via Python, 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.Get 3D data, i.e., z.Create a new figure or activate an existing figure.Get the 3D axes.Create a surface plot.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.linspace(-3, 3, 100) y = np.cos(x) x, y = np.meshgrid(x, y) z = x ** 2 + y ** 2 - 2 ... Read More

How to set the xticklabels for date in matplotlib?

Rishikesh Kumar Rishi
Updated on 02-Feb-2022 10:51:20
To set the xticklabels for date in matplotlib, we can take the following steps −StepsSet the figure size and adjust the padding between and around the subplots.Create two lists of epochs and values.Get a list of dates from epochs.Create a figure and a set of subplots.Plot the date and values using plot() method.Set the xticklabels, get date formatter and set the major formatter.To remove the overlapping for ticklabels, rotate it by 10.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt import matplotlib.dates as mdates import time plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True epochs = [1259969793926, 1259969793927, ... Read More
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