Rishikesh Kumar Rishi

Rishikesh Kumar Rishi

1,016 Articles Published

Articles by Rishikesh Kumar Rishi

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How to prevent numbers being changed to exponential form in Python Matplotlib?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 1K+ Views

Using style='plain' in the ticklabel_format() method, we can restrict the value being changed into exponential form.StepsPass two lists to draw a line using plot() method.Use ticklabel_format() method with style='plain'. If a parameter is not set, the corresponding property of the formatter is left unchanged. Style='plain' turns off scientific notation.To show the figure, use plt.show() method.Examplefrom matplotlib import pyplot as plt plt.plot([1, 2, 3, 4, 5], [11, 12, 13, 14, 15]) plt.ticklabel_format(style='plain')    # to prevent scientific notation. plt.show()Output

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Generating a movie from Python without saving individual frames to files

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 435 Views

Using the FuncAnimation method, we can create a film. We will create a user-defined method, update, to keep on changing the position of particles and at the end, the method would return the scatter instance.StepsGet the particles initial position, velocity, force, and size.Create a new figure, or activate an existing figure with figsize = (7, 7).Add an axes to the current figure and make it the current axes, with xlim and ylim.Plot the scatter for initial position of the particles.Makes an animation by repeatedly calling a function *func*. We can pass a user-defined method that helps to change the position ...

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How to turn on minor ticks only on the y-axis Matplotlib?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 2K+ Views

First, we can create fig, ax using subplots() and then, we can plot the lines. After that, using ax.yaxis.set_minor_locator(tck.AutoMinorLocator()), we can turn on the minor ticks.StepsCreate fig and ax variables using subplots method, where default nrows and ncols are 1.Plot the line using two lists.Set the locator of the minor ticker.Dynamically find minor tick positions based on the positions of major ticks. The scale must be linear with major ticks evenly spaced.Using plt.show() method, we can show the figure.Exampleimport matplotlib.pyplot as plt import matplotlib.ticker as tck fig, ax = plt.subplots() plt.plot([0, 2, 4], [3, 6, 1]) ax.yaxis.set_minor_locator(tck.AutoMinorLocator()) plt.show()Output

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How to zoom subplots together in Matplotlib/Pyplot?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 3K+ Views

We can use the attribute sharex = "ax1", and then, use the subplot method to zoom the subplots together.StepsAdd a subplot to the current figure with (nrow = 1, ncols = 2, index = 1).Add line on the current subplot with (nrow = 1, ncols = 2, index = 1).Add a subplot to the current figure with (nrow = 1, ncols = 2, index = 2).Add line on the current subplot with (nrow = 1, ncols = 2, index = 2), where sharex can help to share the x or y `~matplotlib.axis` with sharex and/or sharey. The axis will have ...

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How do you plot a vertical line on a time series plot in Pandas?

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 4K+ Views

Using Pandas, we will create a dataframe and set the vertical lines on the created axes, using axvline lines.StepsUsing panda we can create a data frame.Creating a data frame would help to create help.Using axvline(), add a vertical line across the axes, where color is green, linestyle="dashed".Using axvline(), add a vertical line across the axes, where color is red, linestyle="dashed".Using plt.show(), show the plot.Exampleimport pandas as pd from matplotlib import pyplot as plt df = pd.DataFrame(index=pd.date_range("2019-07-01", "2019-07-31")) df["y"] = 1 ax = df.plot() ax.axvline("2019-07-24", color="green", linestyle="dashed") ax.axvline("2019-07-31", color="red", linestyle="dashed") plt.show()Output

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Make 3D plot interactive in Jupyter Notebook (Python & Matplotlib)

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 4K+ Views

In this article, we can take a program code to show how we can make a 3D plot interactive using Jupyter Notebook.StepsCreate a new figure, or activate an existing figure.Create fig and ax variables using subplots method, where default nrows and ncols are 1, projection=’3d”.Get x, y and z using np.cos and np.sin function.Plot the 3D wireframe, using x, y, z and color="red".Set a title to the current axis.To show the figure, use plt.show() method.Exampleimport matplotlib.pyplot as plt import numpy as np fig = plt.figure() ax = fig.add_subplot(111, projection='3d') u, v = np.mgrid[0:2 * np.pi:30j, 0:np.pi:20j] x = np.cos(u) * ...

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Multiple axes in Matplotlib with different scales

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 4K+ Views

In the following code, we will see how to create a shared Y-axis.StepsCreate fig and ax variables using subplots method, where default nrows and ncols are 1.Plot line with lists passed in the argument of plot() method with color="red".Create a twin of Axes with a shared X-axis but independent Y-axis.Plot the line on ax2 that is created in step 3.Adjust the padding between and around subplots.To show the figure use plt.show() method.Exampleimport matplotlib.pyplot as plt fig, ax1 = plt.subplots() ax1.plot([1, 2, 3, 4, 5], [3, 5, 7, 1, 9], color='red') ax2 = ax1.twinx() ax2.plot([11, 12, 31, 41, 15], [13, 51, ...

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Making matplotlib scatter plots from dataframes in Python's pandas

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 1K+ Views

Using Pandas, we can create a dataframe and can create a figure and axes variable using subplot() method. After that, we can use the ax.scatter() method to get the required plot.StepsMake a list of the number of students.Make a list of marks that have been obtained by the students.To represent the color of each scattered point, we can have a list of colors.Using Pandas, we can have a list representing the axes of the data frame.Create fig and ax variables using subplots method, where default nrows and ncols are 1.Set the “Students count” label using plt.xlabel() method.Set the “Obtained marks” ...

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Prevent scientific notation in matplotlib.pyplot

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 20K+ Views

To prevent scientific notation, we must pass style='plain' in the ticklabel_format method.StepsPass two lists to draw a line using plot() method.Using ticklabel_format() method with style='plain'. If a parameter is not set, the corresponding property of the formatter is left unchanged. Style='plain' turns off scientific notation.To show the figure, use plt.show() method.Examplefrom matplotlib import pyplot as plt plt.plot([1, 2, 3, 4, 5], [11, 12, 13, 14, 15]) plt.ticklabel_format(style='plain')    # to prevent scientific notation. plt.show()Output

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Manually add legend Items Python Matplotlib

Rishikesh Kumar Rishi
Rishikesh Kumar Rishi
Updated on 17-Mar-2021 23K+ Views

Using plt.legend() method, we can create a legend, and passing frameon would help to keep the border over there.StepsSet the X-axis label using plt.xlabel() method.Set the Y-axis label using plt.ylabel() method.Draw lines using plot() method.Location and legend drawn flags can help to find a location and make the flag True for the border.Set the legend with “blue” and “orange” elements.To show the figure use plt.show() method.Exampleimport matplotlib.pyplot as plt plt.ylabel("Y-axis ") plt.xlabel("X-axis ") plt.plot([9, 5], [2, 5], [4, 7, 8]) location = 0 # For the best location legend_drawn_flag = True plt.legend(["blue", "orange"], loc=0, frameon=legend_drawn_flag) plt.show()Output

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