annotate ( "Point-2", xy = ( 7, 7 ), xytext = ( 9, 9 ), fontsize = 14, fontweight = "bold", # Font settings arrowprops = dict ( arrowstyle = "", facecolor = "black", connectionstyle = "angle3, angleA=90, angleB=0", shrinkA = 10, shrinkB = 10 ) ) plt. annotate ( "Point-1", xy = ( 4, 7 ), xytext = ( 0.5, 9 ), fontsize = 14, fontweight = "bold", # Font settings, arrowprops = dict ( arrowstyle = "->", facecolor = "black", connectionstyle = "bar", shrinkA = 10, shrinkB = 10 ) ) plt. annotate ( "Point-4", xy = ( 4, 4 ), xytext = ( 0.5, 0.5 ), fontsize = 14, fontweight = "bold", # Font settings arrowprops = dict ( arrowstyle = "-", facecolor = "black", shrinkA = 10, shrinkB = 10 ) ) annotate ( "Point-2", xy = ( 7, 7 ), xytext = ( 9, 9 ), fontsize = 14, fontweight = "bold", # Font settings arrowprops = dict ( arrowstyle = "", facecolor = "black", shrinkA = 10, shrinkB = 10 ) ) plt. annotate ( "Point-1", xy = ( 4, 7 ), xytext = ( 0.5, 9 ), fontsize = 14, fontweight = "bold", # Font settings, arrowprops = dict ( arrowstyle = "->", facecolor = "black", shrinkA = 10, shrinkB = 10 ) ) plt. Fancy Arrow - If we specify arrowstyle then fancy arrow will be created which takes many different parameters.īelow, we have added simple arrows to chart.We can specify parameters like width, headwidth, headlength and shrink to modify arrow width, arrowhead width, arrowhead length, and fraction of length to shrink on both sides to avoid overlapping with text and glyphs. Simple Arrow - If we don't specify arrowstyle then simple arrow will be created which is straight arrow.We can create two kinds of arrows using arrowprops parameter. It accepts dictionary specifying various arrow properties. We can specify arrow properties using arrowprops parameter. We can specify arrow start and end points using xy and xytext parameters. Then, we have added text and arrow annotations to chart by calling annotate() function 4 times. The points are laid out in rectangular fashion. We can add text and arrow annotations using annotate() function of pyplot sub-module.īelow, we have first created a simple scatter chart of 4 points.
#ANNOTATE TEXT MATPLOTLIB HOW TO#
In this section, we have explained how to add text and arrow annotations to our matplotlib charts.
#ANNOTATE TEXT MATPLOTLIB FREE#
Please feel free to check below video tutorial if feel comfortable learning through videos.
If you are someone who is new to matplotlib and want to get started with it then we'll recommend that you go through below link which covers basic charts with simple examples. Tutorial expects that reader has a little background with matplotlib. We have explained various annotations like text annotations, text & arrow annotations, span annotations, box annotations, etc. What Can You Learn From This Article? ¶Īs a part of this tutorial, we have explained how to annotate matplotlib charts with simple and easy-to-understand examples. The oldest library of all is matplotlib which let us create publication-ready static charts in Python. Python has a bunch of libraries that let us create all types of charts. Python is the go-to language nowadays to do data analysis and create visualizations.
It'll draw readers' attention to that part. We try to annotate charts using various annotations (like arrows, text, boxes, polygons, bounds, etc) to highlight important parts of the chart. This practice has been carried over to data visualization world as well. This is commonly referred to as annotation. Many of us have a habit of highlighting things with markers when reading books to remember some important part or to bring attention to that part when we next time read it again.
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