Line and Bar Plots

Import Libraries

Seaborn automatically install these libraries in jupyter notebook

numpy
scipy
pandas
matplotlib

In [1]:

# import libraries

import seaborn as sns

import matplotlib.pyplot as plt

#load built-in dataset

flower = sns.load_dataset("iris")

flower # it will show data present in dataset named iris

Out[1]:

	sepal_length	sepal_width	petal_length	petal_width	species
0	5.1	3.5	1.4	0.2	setosa
1	4.9	3.0	1.4	0.2	setosa
2	4.7	3.2	1.3	0.2	setosa
3	4.6	3.1	1.5	0.2	setosa
4	5.0	3.6	1.4	0.2	setosa
�	�	�	�	�	�
145	6.7	3.0	5.2	2.3	virginica
146	6.3	2.5	5.0	1.9	virginica
147	6.5	3.0	5.2	2.0	virginica
148	6.2	3.4	5.4	2.3	virginica
149	5.9	3.0	5.1	1.8	virginica

150 rows � 5 columns

Line Plot

Line plot is always between two numeric values.

In [2]:

# import libraries

import seaborn as sns

import matplotlib.pyplot as plt

#load built-in dataset

flower = sns.load_dataset("iris")

# draw a line plot

sns.lineplot(x="sepal_length",y="petal_length",data=flower)

plt.show()

Title for your plot

In [3]:

# import libraries

import seaborn as sns

import matplotlib.pyplot as plt

#load built-in dataset

flower = sns.load_dataset("iris")

# draw a line plot

sns.lineplot(x="sepal_length",y="petal_length",data=flower)

plt.title(" Flowers Compaison between Sepal Length and Petal Length")

plt.show()

Adding Axix limits

In [4]:

# import libraries

import seaborn as sns

import matplotlib.pyplot as plt

#load built-in dataset

flower = sns.load_dataset("iris")

# draw a line plot

sns.lineplot(x="sepal_length",y="petal_length",data=flower)

plt.xlim(6)

plt.ylim(5)

plt.show()

Adding styles in plot

darkgrod
whitegrid
dark
white
ticks

In [5]:

# import libraries

import seaborn as sns

import matplotlib.pyplot as plt

from matplotlib import style

#load built-in dataset

flower = sns.load_dataset("iris")

# draw a line plot

sns.lineplot(x="sepal_length",y="petal_length",data=flower)

plt.title(" Flowers Compaison between Sepal Length and Petal Length")

sns.set_style("dark")

plt.show()

Size of figure

In [6]:

# import libraries

import seaborn as sns

import matplotlib.pyplot as plt

#load built-in dataset

flower = sns.load_dataset("iris")

#change figure

plt.figure(figsize=(10,4))

# draw a line plot

sns.lineplot(x="sepal_length",y="petal_length",data=flower)

plt.title(" Flowers Compaison between Sepal Length and Petal Length")

plt.show()

Bar Plot

In [7]:

# import libraries

import seaborn as sns

import matplotlib.pyplot as plt

#load built-in dataset

flower = sns.load_dataset("iris")

# draw a line plot

sns.barplot(x="species",y="petal_length",data=flower)

plt.title(" Flowers Compaison between Sepal Length and Petal Length")

plt.show()

In [8]:

# import libraries

import seaborn as sns

import matplotlib.pyplot as plt

#load built-in dataset

boat = sns.load_dataset("titanic")

# draw a line plot

sns.barplot(x="sex",y="alone",hue="who", data=boat)

plt.title(" Flowers Compaison between Sepal Length and Petal Length")

plt.show()

Setting order in plot

In [9]:

# import libraries

import seaborn as sns

import matplotlib.pyplot as plt

#load built-in dataset

boat = sns.load_dataset("titanic")

# draw a line plot

sns.barplot(x="sex",y="alone",hue="who", data=boat, order=["female", "male"])

plt.title(" Flowers Compaison between Sepal Length and Petal Length")

plt.show()

Setting custom Colors in plot

In [10]:

# import libraries

import seaborn as sns

import matplotlib.pyplot as plt

#load built-in dataset

boat = sns.load_dataset("titanic")

# draw a line plot

sns.barplot(x="sex",y="alone",hue="who", data=boat, order=["female", "male"], color = "brown")

plt.title(" Flowers Compaison between Sepal Length and Petal Length")

plt.show()

Remove header bars

In [11]:

# import libraries

import seaborn as sns

import matplotlib.pyplot as plt

#load built-in dataset

boat = sns.load_dataset("titanic")

# draw a line plot

sns.barplot(x="sex",y="alone",hue="who", data=boat, order=["female", "male"], ci=None)

plt.title(" Flowers Compaison between Sepal Length and Petal Length")

plt.show()

Use of Different pallets

In [12]:

# import libraries

import seaborn as sns

import matplotlib.pyplot as plt

#load built-in dataset

boat = sns.load_dataset("titanic")

# draw a line plot

sns.barplot(x="sex",y="alone",hue="who", data=boat, order=["female", "male"],

           palette='pastel')

plt.title(" Flowers Compaison between Sepal Length and Petal Length")

plt.show()

Estimatters

In [14]:

# import libraries

import seaborn as sns

from numpy import mean

import matplotlib.pyplot as plt

#load built-in dataset

boat = sns.load_dataset("titanic")

boat

# draw a line plot

sns.barplot(x="class",y="fare",hue="sex", data=boat, estimator=mean)

plt.show()

In [16]:

# import libraries

import seaborn as sns

from numpy import median

import matplotlib.pyplot as plt

#load built-in dataset

boat = sns.load_dataset("titanic")

boat

# draw a line plot

sns.barplot(x="class",y="fare",hue="sex", data=boat, estimator=median)

plt.show()

Saturation

In [17]:

# import libraries

import seaborn as sns

from numpy import mean

import matplotlib.pyplot as plt

#load built-in dataset

boat = sns.load_dataset("titanic")

boat

# draw a line plot

sns.barplot(x="class",y="fare",hue="sex", data=boat, estimator=mean, saturation=0.5)

plt.show()

Line Plot and Bar Plot in python