Histogram is a graphical representation of the distribution of a dataset, where the data is divided into a set of intervals or bins, and the count of data points that fall into each bin is represented by the height of a bar. Histograms are widely used in data analysis and visualization. Python provides built-in functions to create histograms, and the first argument of the histogram function plays an important role in customizing the histogram.

### Syntax

The syntax of the histogram function in Python is as follows:

numpy.histogram(a, bins=10, range=None, normed=False, weights=None, density=None)

The first argument **a** is the input data that we want to create a histogram of. It can be a list, an array, or a tuple of values. The **bins** parameter specifies the number of bins or intervals to divide the data into. By default, it is set to 10, which means the data will be divided into 10 equal intervals. The **range** parameter specifies the range of data to be included in the histogram. By default, it is set to the minimum and maximum value of the data.

## Use of 1st argument

Now, let's focus on the use of the first argument in the histogram function. The first argument **a** specifies the input data that we want to create a histogram of. It can be a list, an array, or a tuple of values. The histogram function counts the number of data points that fall into each bin and returns the counts and the bins.

### Example

In the case of a list, we can simply pass the list as the first argument of the histogram function. For example:

import numpy as np

data = [1, 2, 3, 3, 4, 5, 5, 6, 6, 6, 7, 8, 8, 8, 8, 9, 9, 10]

hist, bins = np.histogram(data, bins=5)

In this example, we pass the list **data** as the first argument of the histogram function, and the function divides the data into 5 equal intervals or bins. The output of the function is stored in the variables **hist** and** bins**. The **hist** variable contains the counts of data points that fall into each bin, and the **bins** variable contains the boundaries of the bins.

### Example

In the case of an array, we can also pass the array as the first argument of the histogram function. For example:

import numpy as np

data = np.array([1, 2, 3, 3, 4, 5, 5, 6, 6, 6, 7, 8, 8, 8, 8, 9, 9, 10])

hist, bins = np.histogram(data, bins=5)

In this example, we convert the list **data** into an array using the NumPy library and then pass it as the first argument of the histogram function. The output is the same as before.

### Conclusion

In summary, the first argument of the histogram function in Python is used to specify the input data that we want to create a histogram of. It can be a list, an array, or a tuple of values. The histogram function counts the number of data points that fall into each bin and returns the counts and the bins. With this function, we can easily create and customize histograms to analyze and visualize our data.

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