Best Annotation Tools for Matplotlib to Buy in October 2025
Transparent Sticky Notes - 3x3 inch Clear Sticky Notes Waterproof Self-Adhesive Translucent Sticky Note Pads for Books Annotation, See Through Sticky Note (200 Sheets)
- CLEAR DESIGN ENHANCES VISIBILITY: AVOID BLOCKING TEXT, SMOOTH ANNOTATION.
- EASY REPOSITIONING: STICK FIRMLY, REMOVE CLEANLY, IDEAL FOR BOOK LOVERS.
- VERSATILE & PRACTICAL GIFT: PERFECT FOR OFFICES, SCHOOLS, AND FAMILY USE.
ELII 3200pcs Books Tabs for Annotating,Sticky Tabs Clear Sticky Notes, Morandi Page Markers for Notebooks, Multi-Colored Writable and Repositionable Book Flags Strip (3200pcs)
- ENHANCED ORGANIZATION: 16 SETS OF COLORFUL TABS FOR EASY CATEGORIZATION.
- WRITABLE & REPOSITIONABLE: EASILY STICK, REMOVE, AND REWRITE WITHOUT DAMAGE.
- VERSATILE USE: IDEAL FOR DOCUMENTS, NOTES, PLANNERS, AND STUDY MATERIALS.
Sticky Book Tabs with Highlighers, 800 PCS Annotation Tabs for Annotating Books, Moran and di Writable Page Flags Marker, Sticky Notes Index Tabs for Files Classification, 6 PCS Highlighters
- ELEGANT COLORS FOR A SOOTHING READING EXPERIENCE AND BALANCE.
- WATERPROOF DESIGN ENSURES DURABLE, CLEAR ANNOTATIONS EVERY TIME.
- REPOSITIONABLE TABS WON'T TEAR PAGES; PERFECT FOR ANY SETTING.
Mr. Pen- Aesthetic Book Annotation Kit, Aesthetic Highlighters and Gel Pens, Transparent Sticky Notes, Transparent Sticky Tabs for Books, No Bleed Highlighters for Bible Pages No Bleed
- ORGANIZE AND ANNOTATE WITH 16 PASTEL HIGHLIGHTERS-NO BLEED-THROUGH!
- VIBRANT GEL PENS FOR SMOOTH WRITING AND ENHANCED NOTE-TAKING EXPERIENCE.
- 20 STICKY NOTE FLAGS AND VARIOUS SIZES KEEP YOUR STUDY MATERIALS TIDY!
![KICNIC Page Markers Colored Sticky Tabs 800 Pcs, Translucent Arrow Flags for Page Marking, Fluorescent Index Tab Stickers for Notebooks, Small Sticky Notes Flags [8 Colors, 4 Sets]](https://cdn.blogweb.me/1/41_O_Wwcp4mt_L_SL_160_d9430fcbb9.jpg)
KICNIC Page Markers Colored Sticky Tabs 800 Pcs, Translucent Arrow Flags for Page Marking, Fluorescent Index Tab Stickers for Notebooks, Small Sticky Notes Flags [8 Colors, 4 Sets]
- VALUE PACK: 3200 NEON STICKY TABS FOR ALL YOUR MARKING NEEDS!
- DURABLE MATERIAL: WATER-RESISTANT, SMOOTH, AND NO ODOR FOR LASTING USE.
- VERSATILE USE: PERFECT FOR NOTES, BOOKS, FILES, AND COLOR-CODING!
Mr. Pen- Colorful Sticky Tabs, 1600 Pcs, Transparent Page Markers, Annotating Book Tabs
- VERSATILE 1600-PACK: 80 COLORS FOR EFFICIENT DOCUMENT ORGANIZATION!
- WATERPROOF, NON-TOXIC TABS WITH SMOOTH WRITING ON ANY SURFACE!
- REPOSITIONABLE AND REUSABLE, PERFECT FOR HOME, SCHOOL, OR OFFICE!
Jutom 38 Pcs Book Annotation Kit Aesthetic Highlighters Gel Pens Set Sticky Notes Tabs Markers Dual Ended Highlighter Quick Dry Ink Pens for Office Annotating Books(Classic Color,Square)
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ALL-IN-ONE PACK: 500 STICKY NOTES, MARKERS, HIGHLIGHTERS & GEL PENS!
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DURABLE DESIGN: QUALITY MATERIALS ENSURE LONG-LASTING, RELIABLE USE.
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VERSATILE USE: PERFECT FOR HOME, OFFICE, CLASSROOMS, AND MORE!
HAUTOCO 3600pcs Transparent Highlighter Tape, Removable Highlighter Strips Sticky Notes for Annotating Books, Morandi Clear Sticky Page Markers Tabs for Office School Aesthetic Study Supplies
- 3600 DURABLE TABS IN 30 VIBRANT COLORS FOR ALL YOUR ANNOTATING NEEDS!
- TRANSPARENT, WATERPROOF TAPE PRESERVES ORIGINAL TEXT WHILE HIGHLIGHTING.
- REMOVABLE STRIPS LEAVE NO MARKS, KEEPING YOUR BOOKS PRISTINE AND SAFE!
WSCHU 600 Sheets Transparent Sticky Notes, 3 x 3 inch Clear See Through Sticky Notes and Translucent Writable Book Tabs, Annotation kit, for Book Annotation, Office & Study Supplies
- 600PC KIT: CLEAR STICKY NOTES & TABS FOR VERSATILE NOTE-TAKING!
- WATERPROOF & RESIDUE-FREE: QUALITY PET ENSURES EASY REPOSITIONING.
- QUICK-DRY PEN: SMOOTH WRITING REDUCES SMUDGES ON TRANSPARENT NOTES!
To annotate points on a Matplotlib plot, you can use the annotate() function provided by the library. Here is how you can use it:
- Import the necessary libraries: Start by importing the Matplotlib library with import matplotlib.pyplot as plt.
- Create the plot: Use the plt.plot() function to create a plot based on your data.
- Annotate the desired points: To annotate a specific point on the plot, call the plt.annotate() function. Provide the text you want to display as the annotation using the text parameter. Specify the coordinates of the point you want to annotate with the xy parameter, and the coordinates of the text location using the xytext parameter. You can also customize the appearance of the annotation using other optional parameters such as arrowprops for adding arrows to the annotation, fontsize for setting the font size, etc.
- Repeat step 3 for each point you want to annotate.
- Display the plot: Use plt.show() to display the plot with the annotations.
Here's an example code snippet that demonstrates annotating points on a Matplotlib plot:
import matplotlib.pyplot as plt
Create some sample data
x = [1, 2, 3, 4, 5] y = [1, 4, 9, 16, 25]
Create the plot
plt.plot(x, y)
Annotate a point at (3, 9)
plt.annotate('This point here!', xy=(3, 9), xytext=(3.5, 15), arrowprops=dict(facecolor='black', arrowstyle='->'), fontsize=10)
Annotate another point at (4, 16)
plt.annotate('Another point!', xy=(4, 16), xytext=(4.5, 22), arrowprops=dict(facecolor='red', arrowstyle='->'), fontsize=12)
Display the plot
plt.show()
When you run this code, it will create a simple line plot and annotate two points on it. The annotations will have arrows pointing to the specified points, along with the provided text.
How to annotate subplots in a multi-panel figure using matplotlib?
To annotate subplots in a multi-panel figure using matplotlib, you need to create individual annotations for each subplot and provide the necessary coordinates for each annotation. Here is an example code that demonstrates this process:
import matplotlib.pyplot as plt
Create subplots
fig, axes = plt.subplots(nrows=2, ncols=2)
Create data for subplots
x = [1, 2, 3, 4] y = [3, 1, 4, 2]
Plot data and annotate subplots
for ax, i in zip(axes.flat, range(4)): ax.plot(x, y) # plot data ax.set_title(f'Subplot {i+1}') # set subplot title ax.annotate(f'Point {i+1}', xy=(2, 2), xytext=(3, 3), arrowprops=dict(facecolor='black')) # annotate subplot
plt.tight_layout() # adjust subplot spacing plt.show()
In this example, we create a 2x2 subplot grid using the plt.subplots() function. We then generate some data for each subplot and create a line plot using ax.plot(). To annotate each subplot, we use ax.annotate() and provide the text for the annotation ('Point {i+1}'), the xy coordinates of the point being annotated (xy=(2, 2)), and the xy coordinates of the text location (xytext=(3, 3)). We also set arrowprops to customize the appearance of the arrow connecting the point and the text.
Finally, plt.tight_layout() is used to improve the subplot spacing.
What is the syntax for annotating points on a plot in matplotlib?
The syntax for annotating points on a plot in matplotlib is as follows:
import matplotlib.pyplot as plt
Plotting the data
plt.plot(x, y, 'bo')
Annotating points on the plot
plt.annotate('point label', xy=(x, y), xytext=(x_shift, y_shift), arrowprops=dict(facecolor='black', arrowstyle='->'))
Display the plot
plt.show()
Here is a breakdown of the different parts:
- plt.plot(x, y, 'bo') is used to plot the data. x and y are the coordinates of the point, and 'bo' specifies the style of the plot (e.g., blue circles).
- plt.annotate('point label', xy=(x, y), xytext=(x_shift, y_shift), arrowprops=dict(facecolor='black', arrowstyle='->')) is used to annotate a point on the plot. 'point label' is the text label for the annotation, xy=(x, y) specifies the coordinates of the point to annotate, and xytext=(x_shift, y_shift) specifies the coordinates of the text label.
- arrowprops=dict(facecolor='black', arrowstyle='->') is optional and can be used to customize the appearance of the annotation arrow. In this example, it sets the arrow color to black and the arrow style to '->'.
- plt.show() displays the plot.
You can adjust the parameters xytext, xy, x_shift, y_shift, and arrowprops according to your specific requirements.
How to change the color of an annotation in matplotlib?
To change the color of an annotation in matplotlib, you can use the set_color() method. Here's an example:
import matplotlib.pyplot as plt
Plotting the data
x = [1, 2, 3] y = [4, 5, 6] plt.plot(x, y)
Adding an annotation
annotation = plt.annotate('Example', xy=(2, 5), xycoords='data')
Changing the color of the annotation
annotation.set_color('red')
Displaying the plot
plt.show()
In this example, we first plot some data using plot(). Then, we add an annotation using annotate(), specifying the text and position of the annotation. Finally, we use set_color() on the annotation object to change its color to red.