Matplotlib.pyplot.hist2d() in Python
Last Updated :
21 Apr, 2020
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:
from matplotlib import colors
from matplotlib.ticker import PercentFormatter
import numpy as np
import matplotlib.pyplot as plt
N_points = 100000
x = 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()
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Output:
Example #2:
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()
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Output:
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