visualization of data using matplotlib and seaborn
Published: 2022-10-22 22:54:34

## Visualization of data.
Data visualization is the graphical representation of data.
Matplotlib is a python library used in plotting of graphs with other modules such such pandas and numpy while seaborn is also
a python library used for plotting graph with help ofother libararies like matplotlib,numpy and pandas.
The difference between seaborn and matplotlib is that,seaborn 
complies  the entire data into a single plot while matplotlib is
used in plotting 2-D graphs of arrays.
 

1. Matplotlib

 The first  thing is to install matplotlib that uses a simple command

```
pip install matplotlib
```
After matplotlib has being installed you have to import the matplotlib module as shown below

```
import matplotlib.pyplot as plt
```
note: plt is an alias.
Matplotlib is used in plotting varoius graphs such as
             

- bar graphs

- histograms

- pie charts

- scatter plots

Scatter plot

to draw a scatter plot we use the SCATTER() method which draws one dot for each value.To plot a scatter function one should have two values  that is the x-axis values and y-axis values.

```
import matplotlib.pyplot as plt
import numpy as np

xpoints = np.array([3,4,5,7,1,0,5,8,6,4])
ypoints = np.array([70,20,70,30,50,90,55,49,34,28])

plt.scatter(xpoints, ypoints)
plt.show()
```
Bar graphs

when drawing a bar graph we use the BAR() method  to create bar graphs and provide the x-axis and y-axis values.

```
import matplotlib.pyplot as plt
import numpy as np

xvalues = np.array(["mary", "anne", "simon", "james"])
yvalues = np.array([90,10,50,70])

plt.bar(xvalues,yvalues)
plt.show()
```
Histogram

A histogram is a graph that shows frequency distribution.
We use the HIST() method to create histograms, which uses arrays of numbers where the hist function reads the array and provide a histogram.

```
import matplotlib.pyplot as plt
import numpy as np

y = np.random.normal(20, 40, 500)

plt.hist(y)
plt.show()
```
Piechart

We use the pie() method to create pie charts.

```
import matplotlib.pyplot as plt
import numpy as np

z = np.array([10,30,5,60,59,70,2])

plt.pie(z)
plt.show() 
```
The pie chart is subdivided  in 7parts since we have passed 7elements in the array.

2. Seaborn

To use seaborn module you will first install as shown.

```
pip install seaborn
```
after installing you  now import the matplotlib  and seaborn since they go hand in hand.

```
import matplotlib.pyplot as plt 
```

```
import seaborn as sns
```
Seaborn is used in statistical graphics in python now lets load  our data.

```
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df=sns.load_dataset("data")
df
```
Out of our data we can  have a single plot  that describes 
the entire data.

```
import matplotlib.pyplot as plt
import seaborn as sns
sns.pairplot(df)
```
Note:pairplot > allows us to plot pairwise relationships between variables within a dataset.


Distplot in seaborn
Distplot stands for distribution plot it takes as input an array and plots a curve corresponding to the distribution of points in the array.

```
import matplotlib.pyplot as plt
import seaborn as sns

sns.distplot([2,4,6,8,10])

plt.show() 
```