importmatplotlib.pyplotaspltdata=[32,96,45,67,76,28,79,62,43,81,70,61,95,44,60,69,71,23,69,54,76,67,82,97,26,34,18,16,59,88,29,30,66,23,65,72,20,78,49,73,62,87,37,68,81,80,77,92,81,52,43,68,71,86]plt.hist(data)plt.show()

Output:

Understanding the syntax and parameters

Syntax: matplotlib.pyplot.hist(x, bins=None, range=None, density=False, histtype='bar', color=None, label=None)

• x: The data to be represented in the histogram.
• bins: Specifies the number of bins or the bin edges for the histogram.
• range: The lower and upper range of the bins.
• density: If True, the histogram is normalized to form a probability density.
• histtype: Defines the type of histogram (e.g., 'bar' for a traditional bar histogram).
• color: Sets the color of the bars.
• label: Label for the histogram, used in legends.

Create a Histogram in Matplotlib

Using the Matplotlib library in python, we can create many types of histograms. Let us see a few examples to better understand thefunctionality of hist() function. In this example, we will create a histogram and pass the necessary parameters such as bins, color, density, etc.

importmatplotlib.pyplotaspltimportnumpyasnpmu,sigma=121,21x=np.random.normal(mu,sigma,1000)num_bins=100n,bins,_=plt.hist(x,num_bins,density=True,color='green',alpha=0.7)plt.xlabel('X-Axis')plt.ylabel('Y-Axis')plt.title('matplotlib.pyplot.hist() Example',fontweight='bold')plt.show()

Output:

Example 2: Visualize the Specific Bars of Histogram

In this example, we will create a histogram with different attributes using matplotlib.pyplot.hist() function. We define a specific set of colors for the bars of the histogram bars.

importnumpyasnpimportmatplotlib.pyplotaspltx=np.random.randn(10000,3)colors=['green','blue','lime']plt.hist(x,bins=20,density=True,histtype='bar',color=colors,label=colors)plt.legend(fontsize=10)plt.title('matplotlib.pyplot.hist() Example',fontweight='bold')plt.show()

Output: