Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. Pyplot is a state-based interface to a Matplotlib module which provides a MATLAB-like interface.
matplotlib.pyplot.hist2d() Function
The hist2d() function in pyplot module of matplotlib library is used to make a 2D histogram plot.
Syntax:matplotlib.pyplot.hist2d(x, y, bins=10, range=None, density=False, weights=None, cmin=None, cmax=None, \*, data=None, \*\*kwargs)
Parameters: This method accept the following parameters that are described below:
- x, y : These parameter are the sequence of data.
- bins : This parameter is an optional parameter and it contains the integer or sequence or string.
- range : This parameter is an optional parameter and it the lower and upper range of the bins.
- density : This parameter is an optional parameter and it contains the boolean values.
- weights : This parameter is an optional parameter and it is an array of weights, of the same shape as x.
- cmin : This parameter has all bins that has count less than cmin will not be displayed.
- cmax : This parameter has all bins that has count more than cmax will not be displayed.
Returns: This returns the following:
- h :This returns the bi-dimensional histogram of samples x and y.
- xedges :This returns the bin edges along the x axis.
- yedges :This returns the bin edges along the y axis.
- image :This returns the QuadMesh.
Below examples illustrate the matplotlib.pyplot.hist2d() function in matplotlib.pyplot:
Example #1:
# Implementation of matplotlib function from matplotlib import colors from matplotlib.ticker import PercentFormatter import numpy as np import matplotlib.pyplot as plt N_points = 100000x = np.random.randn(N_points) y = 4 * x + np.random.randn(100000) + 50 plt.hist2d(x, y, bins = 100, norm = colors.LogNorm(), cmap ="gray") plt.title('matplotlib.pyplot.hist2d() function \ Example\n\n', fontweight ="bold") plt.show() |
Output:
Example #2:
#Implementation of matplotlib function from matplotlib import colors import numpy as np from numpy.random import multivariate_normal import matplotlib.pyplot as plt result = np.vstack([ multivariate_normal([10, 10], [[3, 2], [2, 3]], size=1000000), multivariate_normal([30, 20], [[2, 3], [1, 3]], size=100000) ]) plt.hist2d(result[:, 0], result[:, 1], bins = 100, cmap = "Greens", norm = colors.LogNorm()) plt.title('matplotlib.pyplot.hist2d function \ Example') plt.show() plt.hist2d(result[:, 0], result[:, 1], bins = 100, cmap = "RdYlGn_r", norm = colors.LogNorm()) plt.show() |
Output:
