seaborn_python library_python_library.pptx

Introduction
to Seaborn
IN TR O DU CTIO N TO S E A B O R
N
Erin Case
Data
Scientist

What is Seaborn?
Python data visualization library
Easily create the most common types of
plots
INTRODUCTION TO SEABORN

Why is Seaborn useful?

Advantages of Seaborn
Easy to
use
Works well
with
Built on top of
pandas data
structures
matplotlib

Getting started
import seaborn as sns
import matplotlib.pyplot as
plt
Samuel Norman Seaborn ( sns )
"The West Wing" television
show

Example 1: Scatter
plot
import matplotlib.pyplot as plt
height = [62, 64, 69, 75,
66,
68, 65, 71, 76, 73]
weight = [120, 136, 148, 175,
137,
165, 154, 172, 200, 187]
sns.scatterplot(x=height,
y=weight) plt.show()

Example 2: Create a count
plot
import matplotlib.pyplot as plt
gender = ["Female", "Female",
"Female", "Female",
"Male", "Male",
"Male",
"Male", "Male",
"Male"]
sns.countplot(x=gender)
plt.show()

Let's
practice!
N

Using pandas
with
Seaborn
N
Erin Case
Data
Scientist

What is pandas?
Python library for data analysis
Easily read datasets from csv, txt, and other types of
files Datasets take the form of DataFrame
objects

Working with DataFrames
import pandas as pd
df =
pd.read_csv("masculinity.csv")
df.head()
0
1
2
3
4
participant_id
1
2
3
4
5
age
18 -
34
18 -
34
18 -
34
18 -
34
18 -
34
how_masculine
Somewhat
Somewhat
Very
Very
Very
how_important
Somewhat
Somewhat
Not
very
Not
very
Very

Using DataFrames with countplot()
import pandas as pd
plt import seaborn as sns
df =
pd.read_csv("masculinity.csv")
sns.countplot(x="how_masculine",
data=df)
plt.show()

Adding a third
variable with
hue
N
Erin Case
Data
Scientist

Tips dataset
import pandas as pd
import seaborn as
sns
tips =
sns.load_dataset("tips")
tips.head()
sex
smoker
0
1
2
3
4
total_bill tip
16.99 1.01
Female
10.34 1.66
Male
21.01 3.50
Male
23.68 3.31
Male
24.59 3.61
day time
size No Sun
Dinner
2
No Sun
Dinner 3
No Sun
Dinner 3
No Sun

A basic scatter
plot
sns.scatterplot(x="total_bill"
,
y="tip",
data=tips)
plt.show()

A scatter plot with hue
,
y="tip",
data=tips,
hue="smoker"
)
plt.show()

Setting hue order
,
y="tip",
data=tips,
hue="smoker",
hue_order=["Yes"
,
"No"]
)
plt.show()

Specifying hue colors
hue_colors = {"Yes": "black",
"No": "red"}
,
y="tip",
data=tips,
hue="smoker",
palette=hue_colors)
plt.show()

Using HTML hex color codes with
hue
hue_colors = {"Yes":
"#808080",
"No": "#00FF00"}
,
y="tip",
data=tips,
hue="smoker",
palette=hue_colors)
plt.show()

Using hue with count plots
sns.countplot(x="smoker",
data=tips,
hue="sex"
)
plt.show()

seaborn_python library_python_library.pptx

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