Connect scatter plot matplotlib4/18/2023 ![]() ![]() The next code section utilizes the 5 steps to build a plot. Note that plt.show() needs to be called after plt.plot() and any plot details such as plt.title(). plt.show() causes the plot to display in a Jupyter notebook or pop out in a new window if the plot is constructed in a separate. Use the plt.show() command to show the plot. Otherwise, the details have no plot to apply to.īesides data, the plt.plot() function can include keyword arguments such as:Īfter the plt.plot() line, add details such as a title, axis labels, legend, grid, and tick labels. Note the plt.plot() line needs to be called before any other plot details are specified. Use plt.plot() to plot the data you defined. Typically, data for plots is contained in Python lists, NumPy arrays or Pandas dataframes. If using a Jupyter notebook, include the line %matplotlib inline in the import section. Import matplot.pyplot as plt, as well as any other modules needed to work with the data such as NumPy or Pandas. The steps below show a logical progression to build a plot with Matplotlib:ĭetails of each step is explained below. The is a Python list or NumPy array of strings. The can be a Python list or NumPy array of tick locations. Tick labels can be specified on a Matplotlib plot using plt.xticks() and plt.yticks(). Note that True and False are capitalized and are not enclosed in quotes. The only valid options are plt.grid(True) and plt.grid(False). Legend LocationĪ grid can be added to a Matplotlib plot using the plt.grid() command. These numbers need to be placed after loc= in the plt.legend() call. The following are the legend location codes. The plt.legend() command accepts a list of strings and optionally accepts a loc= argument to specify the legend location. The legend appears within the plot area, in the upper right corner by default. You can use the plt.legend() command to insert a legend on a plot. The plt.ylabel() command also accepts a string as an argument. The y-axis label is shown to the left of the y-axis. The plt.xlabel() command accepts a string as an argument. The x-axis label is shown below the x-axis. The plt.title() command accepts a string as an argument. The plot title will be shown above the plot. In addition to marker='', the color of the marker edge, the color of the marker face and the size of the marker can be specified with: plt.plot(. color =''īelow is a list of alpha (opacity) values (any alpha value between 0.0 and 1.0 is possible). color =''Ĭolors can also be specified in hexadecimal form surrounded by quotation marks like '#FF69B4' or in RGBA (red, green, blue, opacity) color surrounded by parenthesis like (255,182,193,0.5). Note 'b' is used for blue and 'k' is used for black. ![]() linestyle=''īelow is a list of color abbreviations. linewidth=īelow is a list of line styles. plt.plot(,Īn example plt.plot() function call including line color, line width, and line style options is: plt.plot(x, y,īelow is a list of linewidths (many other widths are also available). Line color, line width, and line style are included as extra keyword arguments in the plt.plot() function call. The color, width, and style of line in a Matplotlib plot can be specified. The following is a list of commonly defined features: Line Color, Line Width, Line Style, Line Opacity and Marker Options Features of a Matplotlib plotĪ variety of features on a Matplotlib plot can be specified. The result is a line plot that shows sin(x) from 0 to 4 \pi. Problem Solving with Python Book Construction Line Color, Line Width, Line Style, Line Opacity and Marker Options ![]()
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