There is extensive text support in Matplotlib that includes support for mathematical expressions, the Truetype support for raster, and vector outputs, also there is a newline-separated text with arbitrary rotations, and Unicode support. Working with Text The Matplotlib library has its own matplotlib.font_manager that is used to implement a cross-platform, W3C compliant font finding algorithm. GivenContinue Reading
In Matplotlib’s mpl_toolkits.mplot3d toolkit there is axes3d present that provides the necessary functions that are very useful in creating 3D surface plots. The representation of a three-dimensional dataset is mainly termed as the Surface Plot. Creation of 3D Surface Plot To create the 3-dimensional surface plot the ax.plot_surface() function is used in matplotlib. The required syntax for this function is given below:Continue Reading
For the data visualization using 3D wireframe, we require some modules from matplotlib, mpl_toolkits and numpy library. The wireframe plot basically takes a grid of values and projects it onto the specified 3-dimensional surfaces, and it can help in making the resulting three-dimensional forms quite easy for visualization. To create the 3D Wireframe plot the plot_wireframe() functionContinue Reading
To draw or to enable the 3d plots you just need to import the mplot3d toolkit. There is a function named ax.contour3D() that is used to create a three-dimensional contour plot. This function requires all the input data to be in the form of two-dimensional regular grids, with its Z-data evaluated at each point. 3D Contour Plot Example InContinue Reading
It is important to note that Matplotlib was initially designed with only two-dimensional plotting in mind. But later on, some three-dimensional plotting utilities were built on top of Matplotlib’s two-dimensional display, which provides a set of tools for three-dimensional data visualization in matplotlib. Also, a 2D plot is used to show the relationshipsContinue Reading
The Violin Plot is used to indicate the probability density of data at different values and it is quite similar to the Matplotlib Box Plot. Here is a figure showing common components of the Box Plot and Violin Plot: Creation of the Violin Plot The violinplot() method is used for the creation of the violinContinue Reading
The box plot in matplotlib is mainly used to displays a summary of a set of data having properties like minimum, first quartile, median, third quartile, and maximum. Creating the Box Plot The Box plot in the matplotlib library is usually created with the help of boxplot() function. The required syntax for the boxplot() function is as follows: Following areContinue Reading
To plot the 2D field of arrows, we use the Quiver plot in the matplotlib library. Creating Matplotlib Quiver Plot In order to create a Quiver Plot the ax.quiver() function is used. The required syntax to use this function is as follows: Following are the parameters of this function, which you can see above in the syntax: Let usContinue Reading
To create a visualization of 3-Dimensional plots in 2-Dimensional space we use contour plots in Matplotlib. Contour plots are also known as Level Plots. Uses of Contour Plot: There are some uses of contour plot given below: Matplotlib contour() Function The function matplotlib.pyplot.contour() is useful when Z = f(X, Y) here, Z changes as a function of input X and Y. A contourf() function is alsoContinue Reading
The Scatter plot is a type of plot that is used to show the data as a collection of points. Matplotlib scatter() Function The method scatter() in the pyplot module in matplotlib library of Python is mainly used to draw a scatter plot. The syntax to use this method is given below: Function Parameters: Let us discuss the parameters of scatter() method:Continue Reading
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