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In this assessment, we will learn how to create histograms using Matplotlib's Pyplot.

Histograms are a special form of bar chart where the data represent continuous rather than discrete categories. This means that in a histogram there are no gaps between the columns representing the different categories. Histogram’s data is plotted within a range against its frequency. Histograms are very commonly occurring graphs in probability and statistics and form the basis for various distributions like the normal -distribution, t-distribution, etc.

Let us start by importing Pyplot:

`import << your code goes here >> as plt`

Now let us create a variable

`x`

with the data that we will use to plot the histogram. Here we will use NumPy’s random.randn() method which generates data with the properties of a standard normal distribution i.e. mean = 0 and standard deviation = 1, and hence the histogram looks like a normal distribution curve.`import << your code goes here >> as np x = np.random.randn(10000)`

Next, we will set up the title and the axis labels:

`plt.<< your code goes here >>("Histogram Example") plt.<< your code goes here >> ("Random Data") plt.<< your code goes here >> ("Frequency")`

Now we will plot our histogram using the

`hist`

method:`plt.<< your code goes here >>(x, 10)`

We have used

`10`

here to divide the data into 10 equal strata or bins.And finally, we will show our plot:

`plt.<< your code goes here >>`

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