# Solved: scatter plot of multiple variables

I’ll provide you a detailed explanation about creating scatter plots for multiple variables in Python. Scatter plots are a great way to visualize the relationships among multiple data points. They help us understand how variables are correlated, how they are distributed and whether they have outlier points.

In Python, multiple libraries provide us with ready-to-use functions to create scatter plots for multiple variables, such as Matplotlib and Seaborn. We will be focusing on these two libraries while solving our problem of deciphering the relationship among multiple data points.

## Introduction to matplotlib and seaborn

Matplotlib is one of the most popular Python plotting libraries that produces quality figures in a variety of formats. It allows us to generate plots, histograms, power spectra, bar charts, error charts, scatter plots, etc., with just a few lines of code.

Seaborn, on the other hand, is based on Matplotlib and closely integrated with pandas data structures. It provides a high-level interface for drawing attractive and informative statistical graphics.

```# Required Libraries
import matplotlib.pyplot as plt
import seaborn as sns
```

## Problem & Solution

For the purpose of this article, let’s assume that you have a dataset with three variables, a, b, and c. You want to create scatter plots that can show the relationships between these variables.

The solution is straightforward, we can use the scatterplot() function in seaborn or scatter() function in matplotlib to create scatter plots. We will also have to further use pairplot() function to make scatter plot of multiple variables.

## Step-by-step explanation

```# Importing libraries
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# Create a pandas DataFrame
df = pd.DataFrame({
'a': [1, 2, 3, 4, 5],
'b': [5, 4, 3, 2, 1],
'c': [1, 3, 5, 7, 9]
})

# Create a pair plot
sns.pairplot(df)
plt.show()
```

In the above code, we first import the required libraries. We then create a DataFrame to hold our data. Finally, we call the pairplot() function from seaborn library to create the scatter plots.

The sns.pairplot() function creates a grid of Axes such that each variable in your data will by shared in the y-axis across a single row and in the x-axis across a single column. In essence, it’s creating scatter plots for every pair of variables for us.

Pandas is another library that often goes hand in hand with Matplotlib and Seaborn. It is an open-source data analysis and manipulation tool, built on top of Python’s core library for data manipulation and analysis.

It provides data structures and functions needed to manipulate structured data, including functions for reading and writing data, handling missing data, filtering data, and reshaping data.

```# Import library
import pandas as pd

# Create a DataFrame