We will have to use the slicing syntax with the iloc function which was discussed in the first section on pandas dataframes.ĥ rows × 41 columns Creating a contour plot # We will pull out the x values, the y values and the data (or the z values as separate variables. For example, at the point (-20, -20), the wavefunction has the value 0.000353. The first row represents x values, and the first column represents y values. You would not automatically know this from looking at the data file, but it is structured in a specific way. We are going to do some additional slicing on this data in order to plot it. The file we are reading in this time does not have headers, so we must tell pandas that there are no headers when we read the data file in. label (cp,fontsize=12,colors=colors) plt.show () Output:-įig.Notice that this time, our function read_csv has not behaved exactly as we would want. Example:- Import numpy as np Import matplotlib.pyplot as plt Import matplotlib.cm as cm X=np.linespace (0, 1,100) Y=x.copy () X, y=np.meshgrid(x,y) Alpha=np.radians (25) Cx,cy=0.5,0.5 Sigx sigy=0.2, 0.3 rx=np.cos(alpha)*(x-cx)-np.sin(alpha)*(y-cy)+cx ry=np.sin(alpha)*(x-cx)+np.cos(alpha)*(y-cy)+cy z=(rx-cx)*np.exp(((rx-cv)/sigx)**2)*np.exp(-((ry-cy/sigy)**2) fig=plt.figure() ax=fig.add_subplot(111) #reversed greys colourmap for filled contours Cpf=ax.contourf(x, y, z, 20, cmap=cm, greys_r) #set the colours of the contours and labels so they are white where the #contour fill is dark (z=0) Colors= Cp=ax. Plt.show () Output:- Simple count plot:- The program will produce a filled contour plot of function, labels contours and will provide some custom styling for colors. Contour() plot has shaded areas produced by ax.contorf() plot.Įxample:- import numpy as np import matplotlib.pyplot as plt # if using a Jupyter notebook, include %matplotlib inline contour method() produce the contour plot that are “filled”. The plt.contourf () method is similar to ax. The code section will include the numpy np.meshgrid () function which will produce the 2D array from two 1D arrays. The contour is represented by color in 2D plot. Where x and y are two dimensional arrays of x and y points and z is the 2d array point that will determine the “height” of contour. While building the counter plot with matplotlib using the ax.counter() method. The line of function has two variables along with the contrast value. The contour line is used in the geographical and mete plot. It is the cross section of the three dimensional graph of function f(x, y) parallel to x, y plane. The contour line of function has two variables with curve and has function of constant value. In the civil engineering the contour plot will show the topology of building slight.Īnd also in the mechanical engineering the contour plot will show the stress gradient across surface. The counter plot Python are the lines used for the geographical and meteorologyĬounter line joints the point of equal height above the grid and the level such as sea level.Ĭounter line of a function is with two variables curve in which counter plots are created. The functions will need three parameters as x, y and z. The matplotlib api contains the contour () and contour () function that will draw contour lines and filled contours both. The meshgrid will create rectangular grid of an array x values and of y values. The independent variables x and the y are restricted to a rectangular grid called as meshgrid. There are two inputs as the x and the y such that z=f(x, y).Ī contour function has two variables and the constant value. The response is given to the z variable as contours and called as z slices or is response values. They will plot the graph with two predictor variables as x, y on y axis. The matplotlib contour plot is also called as level plots and shows the three dimensional surface on two dimensional plane. Learn Contour plot Python Tutorial with example. Contour plot Python Tutorial with example
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