# Create Python Scatter Plot & Python BoxPlot (Using Matplotlib)

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## 1. Python Scatter & BoxPlot

In our Last tutorial, we discussed Python Charts – Bubble & 3D Charts. Today, we will talk Python Scatter Plot. In addition, we will learn how to draw a Scatter Plot in Python Programming. Moreover, we will cover how to create Python Box Plot using Matplotlib.
Let’s begin the Python Scatter Plot.

## 2. How to Create Python BoxPlot Using Matplotlib?

Python box plot tells us how distributed a dataset is. Another use is to analyze how distributed data is across datasets. Such a plot creates a box-and-whisker plot and summarizes many different numeric variables. Let’s first take an example so we can explain its structure better.

```>>> import matplotlib.pyplot as plt
>>> np.random.seed(10)
>>> one=np.random.normal(100,10,200)
>>> two=np.random.normal(80, 30, 200)
>>> three=np.random.normal(90, 20, 200)
>>> four=np.random.normal(70, 25, 200)
>>> to_plot=[one,two,three,four]
>>> fig=plt.figure(1,figsize=(9,6))
>>> bp=ax.boxplot(to_plot)
>>> fig.savefig('boxplot.png',bbox_inches='tight')```

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This saves the following figure-

Structure-

• The box denotes the dataset’s quartiles.
• The whiskers extend and denote the rest of the distribution.
• A function of the inter-quartile range determine the points that are outliers.

The input to this can be a list, a NumPy array, a pandas Series object, an array, a list of vectors, a long-form DataFrame, or a wide-form DataFrame.
Let’s take another example.

```>>> ax = sn.boxplot(x="day", y="total_bill", hue="smoker",data=tips, palette="Set3")
>>> plt.show()``` Creating Python BoxPlot (Using Matplotlib)

## 3. How to Create a Python Scatter Plot?

Python Scatter Plot, let us denote how two or more objects related to each other.

It also lets us identify outliers- values that stray from all others.

```>>> np.random.seed(19680801)
>>> N=50
>>> x=y=colors=np.random.rand(N)
>>> area = (30 * np.random.rand(N))**2
>>> plt.scatter(x, y, s=area, c=colors, alpha=0.5)```

<matplotlib.collections.PathCollection object at 0x095BB6D0>
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`>>> plt.show()`

### a. Python Scatter Plot using plt.plot

```>>> x=np.linspace(0,10,30)
>>> from scipy import sin
>>> y=np.sin(x)
>>> plt.plot(x,y,'o',color='purple')```

[<matplotlib.lines.Line2D object at 0x080D3890>]

`>>> plt.show()`
`>>> plt.plot(x,y,'-ok')`

[<matplotlib.lines.Line2D object at 0x08094F30>]

`>>> plt.show()`
```>>> plt.plot(x,y,'-p',color='green',
markersize=15,linewidth=4,
markerfacecolor='white',
markeredgecolor='gray',
markeredgewidth=1)```

[<matplotlib.lines.Line2D object at 0x0811A4B0>]
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`>>> plt.show()`

### b. More than one plot

`>>> plt.plot(np.random.rand(20),'*')`

[<matplotlib.lines.Line2D object at 0x08158A30>]

```>>> plt.plot(np.random.rand(20),'o')
```

[<matplotlib.lines.Line2D object at 0x08158D90>]D

```>>> plt.show()
``` Draw More than one Scatter Plot in Python

So, this was all about Python Scatter Plot. Hope you like our explanation.

## 4. Conclusion

Hence, we learned how to create Python box plots and scatter plot with matplotlib. Stay tuned for more charts. Leave your opinions in the comments below.
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For reference

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