Best Chart Plotting Tools to Buy in February 2026

1

Dunzoom 3 Pcs Marine Navigation Kit, Basic Navigation Set Include 18" Marine Parallel Ruler with Clear Scales, 8" Diameter Nautical Plotter Protractor, 6" Fixed Point Divider for Boat Accessories

• COMPLETE KIT INCLUDES ESSENTIAL NAVIGATION TOOLS FOR ANY MARINE JOURNEY.
• DURABLE MATERIALS ENSURE ACCURATE READINGS AND LONG-LASTING PERFORMANCE.
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$35.99

2

Mariners Chart Plotting Tool Kit - Marine Navigation Equipment, Weems and Plath Parallel Rulers, Dividers & Accessories for Nautical Charts, Sailing and Boating Exam Preparation

• MASTER NAVIGATION TECHNIQUES WHEN GPS FAILS-STAY ON COURSE!
• COMPLETE KIT: CHARTS, RULER, PENCILS-EVERYTHING FOR ACCURATE PLOTTING.
• IDEAL FOR MARITIME STUDENTS-ACE YOUR SAILING EXAMS WITH CONFIDENCE!

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$100.00

3

MyLifeUNIT Multi-Purpose Drawing Parallel Rolling Ruler, 12 Inch Drawing Design Ruler for Measuring, Drafting

• VERSATILE TOOL: DRAW PARALLEL LINES, CIRCLES, AND ANGLES WITH EASE.
• PRECISION DESIGN: CLEAR SCALE AND BUILT-IN ROLLER ENSURE ACCURATE DRAWING.
• QUICK CALCULATIONS: USE INTEGRATED FORMULAS FOR FAST, ON-THE-GO MEASUREMENTS.

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$7.99

4

Mr. Pen- Professional Compass for Geometry, Extra Lead, Metal Compass, Compass, Compass Drawing Tool, Drawing Compass, Drafting Compass, Compass for Students, Compass Geometry

• HIGH-QUALITY COMPASS FOR PRECISE CIRCLES UP TO 8 INCHES.
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$8.99

5

Weems & Plath Marine Navigation Tool Set (Basic)

• VERSATILE WEEMS PROTRACTOR FOR PRECISE MEASUREMENTS AND DESIGNS.
• DURABLE 15-INCH PARALLEL RULE ENHANCES ACCURACY IN DRAFTING TASKS.
• COMPLETE SET INCLUDES DIVIDER, PENCIL, SHARPENER, AND LIFETIME WARRANTY.

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$69.00 $76.00

Save 9%

6

Weems & Plath Marine Navigation Parallel Plotter

• DURABLE DESIGN ENSURES LONG-LASTING PERFORMANCE FOR SAILORS.
• PRECISION NAVIGATION TOOLS ENHANCE ACCURACY ON EVERY VOYAGE.
• LIGHTWEIGHT AND PORTABLE FOR CONVENIENT USE AT SEA OR ON LAND.

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$39.00

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To add vertical grid lines to a matplotlib chart, you can use the grid method to specify which grid lines you want to display. By default, all grid lines are hidden but can be turned on by setting the which parameter to 'major' or 'minor', depending on whether you want to show the major or minor grid lines.

For vertical grid lines specifically, you would use the axis parameter and set it to 'x' to show vertical grid lines along the x-axis. Additionally, you can customize the appearance of the grid lines by specifying the color, linestyle, and linewidth using the color, linestyle, and linewidth parameters.

Here's an example of how to add vertical grid lines to a matplotlib chart:

import matplotlib.pyplot as plt

Generate some data

x = [1, 2, 3, 4, 5] y = [6, 7, 8, 9, 10]

Create a plot

plt.plot(x, y)

Display vertical grid lines on the x-axis

plt.grid(axis='x', which='both', color='gray', linestyle='--', linewidth=0.5)

Show the plot

plt.show()

This will create a matplotlib chart with vertical grid lines displayed along the x-axis in a gray dashed line style with a linewidth of 0.5.

What is the difference between major and minor vertical grid lines in matplotlib?

In matplotlib, major and minor vertical grid lines refer to the lines that are drawn on the plot to help visually guide the reader in interpreting the data.

Major vertical grid lines are the thicker, more prominent lines that typically represent the larger divisions of the data or axis. They often mark the ends of ticks on the plot and are labeled with larger tick labels.

Minor vertical grid lines, on the other hand, are the thinner, less prominent lines that represent the smaller divisions within the major divisions of the data or axis. They are typically used to provide more detailed guidance to the reader and are labeled with smaller tick labels.

In summary, major vertical grid lines are used to highlight the larger divisions of the data or axis, while minor vertical grid lines are used to highlight the smaller divisions within those larger divisions.

How to customize the appearance of vertical grid lines in matplotlib?

To customize the appearance of vertical grid lines in matplotlib, you can use the grid() function in matplotlib.pyplot and specify the linestyle, color, and width of the grid lines.

Here is an example of customizing the appearance of vertical grid lines:

import matplotlib.pyplot as plt

Create a sample plot

plt.plot([1, 2, 3, 4], [1, 4, 9, 16])

Customize the appearance of vertical grid lines

plt.grid(axis='y', linestyle='--', color='gray', linewidth=0.5)

plt.show()

In this example, the grid() function is used to customize the appearance of the vertical grid lines. The axis parameter is set to 'y' to only display vertical grid lines. The linestyle parameter is set to '--' to specify a dashed line style, the color parameter is set to 'gray' to specify the color of the grid lines, and the linewidth parameter is set to 0.5 to specify the width of the grid lines.

You can further customize the appearance of the grid lines by adjusting the linestyle, color, and linewidth parameters to achieve the desired look for your plot.

How to add vertical grid lines to a polar plot in matplotlib?

To add vertical grid lines to a polar plot in Matplotlib, you can use the grid method of the polar axis object. Here's an example code snippet to demonstrate how to add vertical grid lines to a polar plot:

import matplotlib.pyplot as plt

Create a polar plot

fig, ax = plt.subplots(subplot_kw={'projection': 'polar'}) ax.plot([0, 1, 2, 3, 4], [0, 1, 2, 3, 4])

Add vertical grid lines

ax.set_theta_direction(-1) # Set the theta direction to clockwise ax.grid(True, axis='y') # Add grid lines along the radial axis

plt.show()

In the code above, the set_theta_direction method is used to set the direction of the theta axis to clockwise. The grid method is then called on the polar axis object ax to add grid lines along the radial axis, which creates vertical grid lines in a polar plot.

How to add vertical grid lines at specific x-axis values in matplotlib?

To add vertical grid lines at specific x-axis values in Matplotlib, you can use the axvline function. Here's an example of how you can add vertical grid lines at x-axis values of 2 and 5:

import matplotlib.pyplot as plt

Create a sample plot

x = [1, 2, 3, 4, 5, 6, 7] y = [5, 2, 8, 6, 3, 7, 4] plt.plot(x, y)

Add vertical grid lines at x=2 and x=5

plt.axvline(x=2, color='gray', linestyle='--') plt.axvline(x=5, color='gray', linestyle='--')

plt.show()

In this code snippet, axvline is used to draw vertical lines at x-axis values of 2 and 5 with a gray color and a dashed line style. You can customize the appearance of the vertical grid lines by adjusting the color and linestyle parameters.

How to add vertical grid lines to a log-scale plot in matplotlib?

To add vertical grid lines to a log-scale plot in matplotlib, you can use the grid method to customize the grid lines. Here is an example of how to add vertical grid lines to a log-scale plot:

import matplotlib.pyplot as plt import numpy as np

Generate some sample data

x = np.linspace(1, 10, 100) y = np.log(x)

Create a log-scale plot

plt.figure() plt.plot(x, y) plt.yscale('log')

Customize the grid lines

plt.grid(True, which='both', axis='x', color='gray', linestyle='-', linewidth=0.5)

plt.show()

In this example, we first generate some sample data and create a log-scale plot using the plt.yscale('log') method. We then use the plt.grid method to add vertical grid lines to the plot. The which='both' parameter specifies to show grid lines on both major and minor ticks, and the axis='x' parameter specifies to show grid lines on the x-axis. Finally, we specify the color, linestyle, and linewidth of the grid lines.

You can customize the grid lines further by adjusting the parameters in the plt.grid method to suit your preferences.

How to add vertical grid lines only for specific data points in matplotlib?

To add vertical grid lines only for specific data points in Matplotlib, you can use the axvline() function to draw vertical lines at the specified x-coordinates.

Here's an example code snippet that demonstrates how to add vertical grid lines only for specific data points:

import matplotlib.pyplot as plt

Sample data

x = [1, 2, 3, 4, 5] y = [5, 4, 3, 2, 1]

Scatter plot

plt.scatter(x, y)

Add vertical grid lines for specific data points

for i in [2, 4]: plt.axvline(x=i, color='gray', linestyle='--')

plt.show()

In this code snippet, we first create a scatter plot using the scatter() function with some sample data points. Then, we use a loop to iterate over a list of x-coordinates (in this case, [2, 4]) and add vertical grid lines at those specified x-coordinates using the axvline() function. The color and linestyle arguments are used to customize the appearance of the vertical grid lines.

By running this code, you should see vertical grid lines only for the data points with x-coordinates 2 and 4.