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Articles by Rishikesh Kumar Rishi
Page 22 of 102
How to create a 100% stacked Area Chart with Matplotlib?
To create a 100% stacked Area Chart with Matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a list of years.Make a dictionary, with list of population in respective years.Create a figure and a set of subplots.Draw a stacked Area Plot.Place a legend on the figure, at the location ''upper left''.Set the title, xlabel and ylabel.To display the figure, use show() method.Exampleimport matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True year = [1950, 1960, 1970, 1980, 1990, 2000, 2010, 2018] population_by_continent = { ...
Read MoreCreating 3D animation using matplotlib
To create a 3D animation using matplotlib, we can take the following steps −Import the required packages. For 3D animation, you need to import Axes3D from mpl_toolkits.mplot3d and matplotlib.animation.Set the figure size and adjust the padding between and around the subplots.Create t, x, y and data points using numpy.Create a new figure or activate an existing figure.Get the instance of 3D axes.Turn off the axes.Plot the lines with data.Create an animation by repeatedly calling a function *animate*.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt import matplotlib.animation as animation from mpl_toolkits.mplot3d import Axes3D plt.rcParams["figure.figsize"] ...
Read MoreHow to create broken horizontal bar graphs in matplotlib?
To create broken horizontal bar graphs in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Plot a horizontal sequence of rectangles.Scale X and Y axes limit.Configure the grid lines.Annotate the broken bars.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 fig, ax = plt.subplots() # Horizontal sequence of rectangles ax.broken_barh([(110, 30), (150, 10)], (10, 9), facecolors='tab:blue') ax.broken_barh([(10, 50), (100, 20), (130, 10)], (20, 9), facecolors=('tab:orange', 'tab:green', 'tab:red')) # Scale ...
Read MoreHow to modify a 2d Scatterplot to display color based on a third array in a CSV file?
To modify a 2d scatterplot to display color based on a third array in a CSV file, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Read the CSV file with three headers.Create a new figure or activate an existing figure.Add an 'ax' to the figure as part of a subplot arrangement.Make a scatter plot with CSV file data points.To display the figure, use show() method.Exampleimport pandas as pd from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True columns = ["data1", "data2", "data3"] df = ...
Read MoreMake a multiline plot from .CSV file in matplotlib
To make a multiline plot from .CSV file in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create a list of columns to fetch the data from a .CSV file. Make sure the names match with the column names used in the .CSV file.Read the data from the .CSV file.Plot the lines using df.plot() method.To display the figure, use show() method.Exampleimport pandas as pd from matplotlib import pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Make a list of ...
Read MorePlotting two different arrays of different lengths in matplotlib
To plot two different arrays of different lengths in matplotlib, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create y1, x1, y2 and x2 data points using numpy with different array lengths.Plot x1, y1 and x2, y2 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"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True y1 = (np.random.random(100) - 0.5).cumsum() y2 = y1.reshape(-1, 10).mean(axis=1) x1 = np.linspace(0, 1, 100) x2 = np.linspace(0, 1, 10) plt.plot(x1, y1) plt.plot(x2, y2) ...
Read MoreHow to shift a graph along the X-axis in matplotlib?
To shift a graph along the X-axis in matplotlib, we can take the following steps −Set 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 for the original curve.Plot the shifted graph, in the range of (1, 1+len(y)) with y data points.Place a legend on the figure.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # x and y data points x = np.linspace(-5, 5, ...
Read MoreMatplotlib – How to set xticks and yticks with imshow plot?
To set xticks and yticks with imshow() plot, we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Get the current axis.Create a random dataset.Display the data as an image, i.e., on a 2D regular raster.Set x and y ticks using set_xticks() and set_yticks() method.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True ax = plt.gca() data = np.random.rand(6, 6) ax.imshow(data) # Set xticks and yticks ax.set_xticks([1, 2, 3, 4, 5]) ax.set_yticks([1, 2, 3, 4, 5]) ...
Read MoreRemove white border when using subplot and imshow in Python Matplotlib
To remove white border when using subplot and imshow(), we can take the following steps −Set the figure size and adjust the padding between and around the subplots.Create random data points using numpy.Get the size of the data.Set the figure sizes in inches.Get the axes instance that contains most of the figure element.Turn off the axes.Add axes to the figure.Display the data as an image, i.e., on a 2D regular raster.To display the figure, use show() method.Exampleimport numpy as np import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True data = np.random.randint(0, 50, (50, 50)) sizes ...
Read MoreHow to show tick labels on top of a matplotlib plot?
To show tick labels on top of a matplotlib plot, we can use the set_tick_params() method with labeltop=True.StepsSet the figure size and adjust the padding between and around the subplots.Create a figure and a set of subplots.Show the tick labels at the top of the plot. Use set_tick_parama() with labeltop=True.Hide the tick labels of the bottom axis of plot. Use set_tick_parama() with labeltop=False.To display the figure, use show() method.Examplefrom matplotlib import pyplot as plt # Set the figure size plt.rcParams["figure.figsize"] = [7.00, 3.50] plt.rcParams["figure.autolayout"] = True # Create subplots fig, ax = plt.subplots(1, 1) # Show the ...
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