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Introduction to Data Visualization with Seaborn
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• ```.mfe-app-workspace-11z5vno{font-family:JetBrainsMonoNL,Menlo,Monaco,'Courier New',monospace;font-size:13px;line-height:20px;}```# Importing the course packages
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

# Importing the course datasets

Add notes about the concepts you've learned and code cells with code you want to keep.

``# Add your code snippets here``

### Explore Datasets

Use the DataFrames imported in the first cell to explore the data and practice your skills!

• From `country_data`, create a scatter plot to look at the relationship between GDP and Literacy. Use color to segment the data points by region.
• Use `mpg` to create a line plot with `model_year` on the x-axis and `weight` on the y-axis. Create differentiating lines for each country of origin (`origin`).
• Create a box plot from `student_data` to explore the relationship between the number of failures (`failures`) and the average final grade (`G3`).
• Create a bar plot from `survey` to compare how `Loneliness` differs across values for `Internet usage`. Format it to have two subplots for gender.

## INTRODUCTION TO SEABORN

#### Student data

``student_data``
``````sns.relplot(x="G1",
y="G3",
data=student_data,
kind="scatter",
hue="sex")

plt.show()``````
``````sns.relplot(x="G1",
y="G3",
data=student_data,
kind="scatter",
col="schoolsup",
hue="sex",
palette={"F": "red", "M": "blue"})

plt.show()``````
``````sns.relplot(data=student_data,
x="G1",
y="G3",
col="schoolsup",
row="famsup",
hue="location",
palette={"Rural": "green", "Urban": "blue"})

plt.show()``````
``````sns.countplot(data=student_data,
y="study_time",
hue="sex",
palette={"F":"red", "M":"blue"})

plt.show()``````

## RELATIONAL PLOTS

#### MPG

``mpg``
``````sns.relplot(x="horsepower",
y="mpg",
data=mpg,
kind="scatter",
size="cylinders",
hue="cylinders")

plt.show()``````
``````sns.relplot(x="horsepower",
y="mpg",
data=mpg,
kind="scatter",
hue="origin",
style="origin")

plt.show()``````