Best Plotting Tools to Buy in January 2026
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
- ALL-IN-ONE NAVIGATION KIT: ESSENTIAL TOOLS FOR ACCURATE MARINE NAVIGATION.
- DURABLE & RELIABLE DESIGN: CRAFTED FOR PRECISION AND LONG-LASTING USE.
- CONVENIENCE & SIMPLICITY: ENHANCE YOUR SAILING EXPERIENCE EFFORTLESSLY.
WEEMS & PLATH Essentials Navigation Kit
- ULTRALIGHT DIVIDER FOR PRECISE MEASUREMENTS IN ANY CONDITIONS.
- WEEMS PARALLEL PLOTTER ENSURES ACCURATE NAVIGATION AND PLOTTING.
- NAUTICAL SLIDE RULE SIMPLIFIES COMPLEX CALCULATIONS ON THE GO.
Weems & Plath #176 Marine Navigation Ultralight Divider
- CORROSION-RESISTANT MARINE ALLOY FOR DURABILITY AND LONGEVITY.
- EFFORTLESS OPERATION WITH CENTER GEAR MECHANISM FOR EASY USE.
- TRUSTWORTHY GERMAN ENGINEERING BACKED BY A LIFETIME WARRANTY.
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: ESSENTIAL TOOLS WHEN GPS FAILS OR IS UNRELIABLE.
- COMPLETE KIT: PREMIUM TOOLS FOR PRECISE NAUTICAL PLOTTING ON-THE-GO.
- IDEAL FOR STUDENTS: PERFECT FOR EXAM PREP AND MARITIME TRAINING.
Weems & Plath Marine Navigation Primary Navigation Set
- ULTRALIGHT DIVIDER/COMPASS FOR ACCURATE NAVIGATIONAL PRECISION.
- 12-INCH PARALLEL RULER ENSURES PERFECT LINE AND ANGLE ACCURACY.
- INCLUDES DURABLE STORAGE POUCH FOR EASY ORGANIZATION AND TRANSPORT.
Saypacck Marine Navigation Slide Rule Nautical Plotter Protractor Ship Navigation Tools Course Plotter Divider
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ACCURATE MARINE NAVIGATION: PRECISION PLOTTING ON NAUTICAL CHARTS MADE EASY.
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DURABLE DESIGN: FLEXIBLE PVC WITHSTANDS HARSH MARINE CONDITIONS EFFORTLESSLY.
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SPEED & DISTANCE SIMPLIFIED: QUICK CALCULATIONS SAVE TIME AND ENHANCE EFFICIENCY.
To set the plotting area size in matplotlib, you can use the figure function to create a figure object and specify the size of the figure using the figsize parameter. This parameter takes a tuple of two values, where the first value represents the width of the figure and the second value represents the height of the figure.
For example, if you want to create a figure with a width of 10 inches and a height of 5 inches, you can use the following code:
import matplotlib.pyplot as plt
plt.figure(figsize=(10, 5))
You can then create your plot within this figure object, and the plotting area will be of the specified size. Adjusting the size of the figure can help you control the aspect ratio of your plots and ensure that they are displayed in the desired dimensions.
How to adjust the size of the axes labels in matplotlib?
To adjust the size of the axes labels in Matplotlib, you can use the fontsize parameter in the set_xlabel and set_ylabel functions. Here is an example code snippet:
import matplotlib.pyplot as plt
Create a plot
plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
Set x-axis label with fontsize
plt.xlabel('X-axis label', fontsize=14)
Set y-axis label with fontsize
plt.ylabel('Y-axis label', fontsize=14)
plt.show()
In this example, the fontsize parameter is set to 14 for both x-axis and y-axis labels. You can adjust the font size by changing the value of the fontsize parameter.
How to increase the size of the axis label font in matplotlib?
You can increase the size of the axis label font in matplotlib by using the following code snippet:
import matplotlib.pyplot as plt
Create a plot
plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
Increase the size of the axis label font
plt.xlabel('X-axis Label', fontsize=14) # Change the font size as needed plt.ylabel('Y-axis Label', fontsize=14) # Change the font size as needed
Show the plot
plt.show()
In the code snippet above, you can adjust the fontsize parameter in the plt.xlabel() and plt.ylabel() functions to increase the size of the axis label font.
How to adjust the aspect ratio of the axes in matplotlib?
You can adjust the aspect ratio of the axes in matplotlib by using the set_aspect method. This method allows you to set the aspect ratio of the plot by specifying a ratio value or a string indicating the aspect ratio mode.
Here is an example of how to adjust the aspect ratio of the axes in matplotlib:
import matplotlib.pyplot as plt
Generate some random data
x = [1, 2, 3, 4, 5] y = [10, 15, 13, 18, 16]
Create a scatter plot
plt.scatter(x, y)
Set the aspect ratio of the plot to be equal
plt.gca().set_aspect('equal')
Show the plot
plt.show()
In this example, we create a scatter plot of some random data and then use the set_aspect method to set the aspect ratio of the plot to be equal. You can also specify a specific aspect ratio value if you want to adjust the aspect ratio to a specific ratio.
How to change the size of the axis tick marks in matplotlib?
You can change the size of the axis tick marks in Matplotlib by using the tick_params() function. Here is an example code snippet that demonstrates how to do this:
import matplotlib.pyplot as plt
Create a simple plot
x = [1, 2, 3, 4, 5] y = [2, 3, 5, 7, 11] plt.plot(x, y)
Change the size of the axis tick marks
plt.tick_params(axis='both', which='major', labelsize=10)
plt.show()
In this example, the tick_params() function is used to change the size of the major axis tick marks to 10. You can adjust the labelsize parameter to change the size of the tick marks to your desired value. You can also customize other properties of the tick marks, such as their color, length, width, etc., by passing additional parameters to the tick_params() function.
How to adjust the size of the plot grid in matplotlib?
You can adjust the size of the plot grid in matplotlib by setting the figure size when creating a new Figure object using the plt.figure() function. You can specify the size of the figure by passing a tuple of width and height values in inches to the figsize parameter.
Here is an example code snippet that demonstrates how to adjust the size of the plot grid in matplotlib:
import matplotlib.pyplot as plt
Create a new Figure object with a size of 8x6 inches
plt.figure(figsize=(8, 6))
Plot some data
plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
Display the plot
plt.show()
In this example, a new Figure object is created with a size of 8x6 inches using the plt.figure(figsize=(8, 6)) function call. This will result in a larger plot grid compared to the default size. You can adjust the width and height values to get the desired size for your plot grid.