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Programming Articles
Page 2237 of 2547
How to find the number of unique values for each column in data.table object in R?
To find the number of unique values for each column in data.table object, we can use uniqueN function along with lapply. For example, if we have a data.table object called DT that contains five columns each containing some duplicate values then the number of unique values in each of these columns can be found by using DT[,lapply(.SD,uniqueN)].ExampleConsider the below data.table object −x1
Read MoreAdding textures to graphs using Matplotlib
In this program, we will plot a bar graph using the matplotlib library. The most important Step in solving matplotlib related problems using the matplotlib library is importing the matplotlib library. The syntax is:import matplotlib.pyplot as pltPyplot is a collection of command style functions that make Matplotlib work like MATLAB. In addition to plotting the bar graphs, we will also add some textures to the graphs. The 'hatch' parameter in the bar() function is used to define the texture of the barAlgorithmStep 1: Define a list of values. Step 2: Use the bar() function and define parameters like xaxis, yaxis, ...
Read MoreHow to show two figures using Matplotlib?
We can use the method, plt.figure(), to create the figures, and then, set their titles by passing strings as arguments.StepsCreate a new figure, or activate an existing figure, with the window title “Welcome to figure 1”.Draw a line using plot() method, over the current figure.Create a new figure, or activate an existing figure, with the window title “Welcome to figure 2”.Draw a line using plot() method, over the current figure.Using plt.show(), show the figures.Examplefrom matplotlib import pyplot as plt plt.figure("Welcome to figure 1") plt.plot([1, 3, 4]) plt.figure("Welcome to figure 2") plt.plot([11, 13, 41]) plt.show()Output
Read MorePlotting a 3d cube, a sphere and a vector in Matplotlib
Get fig from plt.figure() and create three different axes using add_subplot, where projection=3d.Set up the figure title using ax.set_title("name of the figure"). Use the method ax.quiver to plot vector projection, plot3D for cube, and plot_wireframe for sphere after using sin and cos.StepsCreate a new figure, or activate an existing figure.To draw vectors, get a 2D array.Get a zipped object.Add an ~.axes.Axes to the figure as part of a subplot arrangement, with 3d projection, where nrows = 1, ncols = 3 and index = 1.Plot a 3D field of arrows.Set xlim, ylim and zlim.Set the title of the axis (at index ...
Read MorePlot width settings in ipython notebook
Using plt.rcParams["figure.figsize"], we can get the width setting.StepsTo get the plot width setting, use plt.rcParams["figure.figsize"] statement.Override the plt.rcParams["figure.figsize"] with a tuple (12, 9).After updating the width, get the updated width using plt.rcParams["figure.figsize"].ExamplesIn IDEExampleimport matplotlib.pyplot as plt print("Before, plot width setting:", plt.rcParams["figure.figsize"]) plt.rcParams["figure.figsize"] = (12, 9) print("Before, plot width setting:", plt.rcParams["figure.figsize"])OutputBefore, plot width setting: [6.4, 4.8] Before, plot width setting: [12.0, 9.0]In IPythonExampleIn [1]: from matplotlib import pyplot as plt In [2]: plt.rcParams["figure.figsize"]OutputOut[2]: [6.4, 4.8]
Read MoreHow to animate a scatter plot in Matplotlib?
Using the FuncAnimation method of matplotlib, we can animate the diagram. We can pass a user defined method where we will be changing the position of the particles, and at the end, we will return plot type.StepsGet the particle's initial position, velocity, force, and size.Create a new figure, or activate an existing figure with figsize = (7, 7).Add an axes to the current figure and make it the current axes, with xlim and ylim.Plot scatter for initial position of the particles.Make an animation by repeatedly calling a function *func*. We can pass a user-defined method that helps to change the ...
Read MoreHow to set the current figure in Matplotlib?
Using the figure() method, we can set the current figure.StepsCreate a new figure, or activate an existing figure, with the window title “Welcome to figure 1”.Create a new figure, or activate an existing figure, with the window title “Welcome to figure 2”.Using plt.show(), show the figures.Examplefrom matplotlib import pyplot as plt plt.figure("Welcome to figure 1") plt.figure("Welcome to figure 2") # Active Figure plt.show()Output
Read MoreHow can I make a scatter plot colored by density in Matplotlib?
We can create a dict for color and a value. If the same value comes up, we can use a scatter method and if the closer values have the same set of colors, that could make the plot color denser.StepsCreate a new figure, or activate an existing figure.Add an ~.axes.Axes to the figure as part of a subplot arrangement.Get the x and y values using np.random.normal() method. Draw random samples from a normal (Gaussian) distribution.Make a color list with red and blue colors.To make it denser, we can store the same color with the same value.Plot scatter point, a scatter ...
Read MoreHow can I plot a histogram such that the heights of the bars sum to 1 in matplotlib?
In plt.hist() method, stacked=True could help to get the heights of the bars sum to 1.StepsCreate a list of numbers.Using plt.hist(), we can draw the histogram.stacked : bool, default: FalseIf "True", multiple data are stacked on top of each other If ``False`` multiple data are arranged side by side if histtype is 'bar' or on top of each other if histtype is 'step'.density : bool, default: FalseIf "True", draw and return a probability density: each bin will display the bin's raw count divided by the total number of counts *and the bin width*.To show the figure, use the plt.show() method.Examplefrom ...
Read MoreHow can I plot NaN values as a special color with imshow in Matplotlib?
First, we can create an array matrix with some np.nan value, and using imshow method, we can create a diagram for that matrix.StepsCreate a new figure, or activate an existing figure.Add an `~.axes.Axes` to the figure as part of a subplot arrangement, nrows = 1, ncols = 1, index = 1.Create a 2D array with np.nan.Display data as an image, i.e., on a 2D regular raster.Use the draw() method which draws the drawing at the given location.To show the figure, use the plt.show() method.Exampleimport numpy as np import matplotlib.pyplot as plt f = plt.figure() ax = f.add_subplot(111) a = ...
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