Question
Write a data visualization script using Matplotlib to build a single Figure containing two side-byside subplot Axes grids: • Subplot 1: A line chart representing trend progression values over a timeline. • Subplot 2: A scatter plot diagram highlighting coordinate cluster spaces. Note: Add clear axis titles, customised colour mappings, legends, and bounding grid markers across the visual plots
Answer :
Word Count : 1108
Matplotlib is a widely used Python library for creating static, interactive, and animated data visualizations. It provides flexible tools for representing numerical data through line charts, scatter plots, bar charts, histograms, and many other graphical forms. The following script creates a single Figure containing two side-by-side subplot Axes. The first subplot uses a line chart to represent the progression of values over a timeline, while the second subplot uses a scatter plot to display coordinate cluster spaces. Customized colour mappings, legends, axis titles, grid markers, and other visual properties are included to make the visualization clear and informative. ```python import matplotlib.pyplot as plt import numpy as np # --------------------------------------------------------- # Data for Subplot 1: Trend progression over a timeline # --------------------------------------------------------- timeline = np.array([ "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct" ]) trend_values = np.array([ 25, 31, 29, 38, 45, 50, 57, 55, 65, 72 ]) # --------------------------------------------------------- # Data for Subplot 2: Coordinate clusters # --------------------------------------------------------- cluster_1_x = np.array([1, 2, 2.5, 3, 3.5, 4]) cluster_1_y = np.array([1, 1.5, 2, 2.2, 2.8, 3]) cluster_2_x = np.array([6, 6.5, 7, 7.5, 8, 8.5]) cluster_2_y = np.array([6, 6.8, 7.2, 7.5, 8.2, 9]) cluster_3_x = np.array([3, 3.5, 4, 4.5, 5, 5.5]) cluster_3_y = np.array([7, 7.5, 8, 8.5, 8.2, 9]) # --------------------------------------------------------- # Create one Figure with two side-by-side Axes # --------------------------------------------------------- fig, ______ _______ _______ _______ __________ _____ _______ ___ _______.
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Matplotlib is a widely used Python library for creating static, interactive, and animated data visualizations. It provides flexible tools for representing numerical data through line charts, scatter plots, bar charts, histograms, and many other graphical forms. The following script creates a single Figure containing two side-by-side subplot Axes. The first subplot uses a line chart to represent the progression of values over a timeline, while the second subplot uses a scatter plot to display coordinate cluster spaces. Customized colour mappings, legends, axis titles, grid markers, and other visual properties are included to make the visualization clear and informative. ```python import matplotlib.pyplot as plt import numpy as np # --------------------------------------------------------- # Data for Subplot 1: Trend progression over a timeline # --------------------------------------------------------- timeline = np.array([ "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct" ]) trend_values = np.array([ 25, 31, 29, 38, 45, 50, 57, 55, 65, 72 ]) # --------------------------------------------------------- # Data for Subplot 2: Coordinate clusters # --------------------------------------------------------- cluster_1_x = np.array([1, 2, 2.5, 3, 3.5, 4]) cluster_1_y = np.array([1, 1.5, 2, 2.2, 2.8, 3]) cluster_2_x = np.array([6, 6.5, 7, 7.5, 8, 8.5]) cluster_2_y = np.array([6, 6.8, 7.2, 7.5, 8.2, 9]) cluster_3_x = np.array([3, 3.5, 4, 4.5, 5, 5.5]) cluster_3_y = np.array([7, 7.5, 8, 8.5, 8.2, 9]) # --------------------------------------------------------- # Create one Figure with two side-by-side Axes # --------------------------------------------------------- fig, ______ _______ _______ _______ __________ _____ _______ ___ _______.
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