Seaborn and Matplotlib Course notebook

Matplotlib¶

In [ ]:

import numpy as np
import matplotlib.pyplot as plt

# Generate data
x = np.linspace(0, 2*np.pi, 100)
y = np.sin(x)

# Plot data
plt.plot(x, y)

# Show plot
plt.show()

import numpy as np import matplotlib.pyplot as plt # Generate data x = np.linspace(0, 2*np.pi, 100) y = np.sin(x) # Plot data plt.plot(x, y) # Show plot plt.show()

In [ ]:

import matplotlib.pyplot as plt

# Data
x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]

# Plot data
plt.plot(x, y)

# Show plot
plt.show()

import matplotlib.pyplot as plt # Data x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8, 10] # Plot data plt.plot(x, y) # Show plot plt.show()

In [ ]:

import matplotlib.pyplot as plt

# Data
x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]

# Plot data
plt.scatter(x, y)

# Show plot
plt.show()

import matplotlib.pyplot as plt # Data x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8, 10] # Plot data plt.scatter(x, y) # Show plot plt.show()

In [ ]:

import matplotlib.pyplot as plt

# Data
x = ['A', 'B', 'C', 'D', 'E']
y = [2, 4, 6, 8, 10]

# Plot data
plt.bar(x, y)

# Show plot
plt.show()

import matplotlib.pyplot as plt # Data x = ['A', 'B', 'C', 'D', 'E'] y = [2, 4, 6, 8, 10] # Plot data plt.bar(x, y) # Show plot plt.show()

In [ ]:

import matplotlib.pyplot as plt

# Data
x = ['A', 'B', 'C', 'D', 'E']
y = [2, 4, 6, 8, 10]

# Plot data
plt.barh(x, y)

# Show plot
plt.show()

import matplotlib.pyplot as plt # Data x = ['A', 'B', 'C', 'D', 'E'] y = [2, 4, 6, 8, 10] # Plot data plt.barh(x, y) # Show plot plt.show()

In [ ]:

import numpy as np
import matplotlib.pyplot as plt

# Data
x = np.random.randn(1000)

# Plot data
plt.hist(x, bins=100)

# Show plot
plt.show()

import numpy as np import matplotlib.pyplot as plt # Data x = np.random.randn(1000) # Plot data plt.hist(x, bins=100) # Show plot plt.show()

In [ ]:

import matplotlib.pyplot as plt
import numpy as np

y = np.array([35, 25, 25, 15])
plt.pie(y) 
plt.show()

import matplotlib.pyplot as plt import numpy as np y = np.array([35, 25, 25, 15]) plt.pie(y) plt.show()

In [ ]:

import matplotlib.pyplot as plt

# Data
x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]

# Plot data
plt.plot(x, y, color='green')

# Add title and labels
plt.title('Line Plot')
plt.xlabel('X Axis')
plt.ylabel('Y Axis')

# Show plot
plt.show()

import matplotlib.pyplot as plt # Data x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8, 10] # Plot data plt.plot(x, y, color='green') # Add title and labels plt.title('Line Plot') plt.xlabel('X Axis') plt.ylabel('Y Axis') # Show plot plt.show()

In [ ]:

import matplotlib.pyplot as plt

# Data
x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]

# Get the weight of each point
z = np.random.rand(5)

# Plot using color map 
plt.scatter(x, y, c=z ,cmap='plasma')
plt.colorbar()

import matplotlib.pyplot as plt # Data x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8, 10] # Get the weight of each point z = np.random.rand(5) # Plot using color map plt.scatter(x, y, c=z ,cmap='plasma') plt.colorbar()

Out[ ]:

<matplotlib.colorbar.Colorbar at 0x7f4698040f40>

In [ ]:

import matplotlib.pyplot as plt

# Data
x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]

# Plot data
plt.plot(x, y, linestyle='--', marker='o', markersize=8)

# Add title and labels
plt.title('Line Plot', color='red')
plt.xlabel('X Axis')
plt.ylabel('Y Axis')

# Show plot
plt.show()

import matplotlib.pyplot as plt # Data x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8, 10] # Plot data plt.plot(x, y, linestyle='--', marker='o', markersize=8) # Add title and labels plt.title('Line Plot', color='red') plt.xlabel('X Axis') plt.ylabel('Y Axis') # Show plot plt.show()

In [ ]:

import matplotlib.pyplot as plt

# Data
x = [1, 2, 3, 4, 5]
y1 = [2, 4, 6, 8, 10]
y2 = [3, 5, 7, 9, 11]
y3= [-3, 5, 4, 9, 1]
y4 = [2, -4, 7, 4, 10]

# Plot data
fig, axs = plt.subplots(2, 2, figsize=(8, 4))

# first figure
axs[0][0].plot(x, y1)
# Add title to first figure
axs[0][0].set_title('Plot 1')

# second figure
axs[0][1].plot(x, y2)
# Add title to second figure
axs[0][1].set_title('Plot 2')

# third figure
axs[1][0].plot(x, y3)
# Add title to third figure
axs[1][0].set_title('Plot 3')


# third figure
axs[1][1].plot(x, y4)
# Add title to third figure
axs[1][1].set_title('Plot 4')


# Show plot
plt.show()

import matplotlib.pyplot as plt # Data x = [1, 2, 3, 4, 5] y1 = [2, 4, 6, 8, 10] y2 = [3, 5, 7, 9, 11] y3= [-3, 5, 4, 9, 1] y4 = [2, -4, 7, 4, 10] # Plot data fig, axs = plt.subplots(2, 2, figsize=(8, 4)) # first figure axs[0][0].plot(x, y1) # Add title to first figure axs[0][0].set_title('Plot 1') # second figure axs[0][1].plot(x, y2) # Add title to second figure axs[0][1].set_title('Plot 2') # third figure axs[1][0].plot(x, y3) # Add title to third figure axs[1][0].set_title('Plot 3') # third figure axs[1][1].plot(x, y4) # Add title to third figure axs[1][1].set_title('Plot 4') # Show plot plt.show()

In [ ]:

plt.savefig('figure.png')

plt.savefig('figure.png')

<Figure size 432x288 with 0 Axes>

Seaborn¶

In [ ]:

import seaborn as sns
import matplotlib.pyplot as plt

tips = sns.load_dataset('tips')

import seaborn as sns import matplotlib.pyplot as plt tips = sns.load_dataset('tips')

In [ ]:

tips.head()

tips.head()

Out[ ]:

	total_bill	tip	sex	smoker	day	time	size
0	16.99	1.01	Female	No	Sun	Dinner	2
1	10.34	1.66	Male	No	Sun	Dinner	3
2	21.01	3.50	Male	No	Sun	Dinner	3
3	23.68	3.31	Male	No	Sun	Dinner	2
4	24.59	3.61	Female	No	Sun	Dinner	4

In [ ]:

sns.scatterplot(x='total_bill', y='tip', data=tips)
plt.show()

sns.scatterplot(x='total_bill', y='tip', data=tips) plt.show()

In [ ]:

sns.lineplot(x='size', y='total_bill', data=tips)
plt.show()

sns.lineplot(x='size', y='total_bill', data=tips) plt.show()

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sns.barplot(x='day', y='total_bill', data=tips)
plt.show()

sns.barplot(x='day', y='total_bill', data=tips) plt.show()

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sns.histplot(x='total_bill', data=tips)
plt.show()

sns.histplot(x='total_bill', data=tips) plt.show()

In [ ]:

sns.boxplot(x='day', y='total_bill', data=tips[tips['total_bill']<40])
plt.show()

sns.boxplot(x='day', y='total_bill', data=tips[tips['total_bill']<40]) plt.show()

In [ ]:

sns.violinplot(x='day', y='total_bill', data=tips)
plt.show()

sns.violinplot(x='day', y='total_bill', data=tips) plt.show()

In [ ]:

import seaborn as sns
import pandas as pd

iris = sns.load_dataset('iris')
iris.head()

import seaborn as sns import pandas as pd iris = sns.load_dataset('iris') iris.head()

Out[ ]:

	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

In [ ]:

sns.pairplot(iris, hue='species')

sns.pairplot(iris, hue='species')

Out[ ]:

<seaborn.axisgrid.PairGrid at 0x7f4664d82910>

In [ ]:

iris.head()

iris.head()

Out[ ]:

	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

In [ ]:

# Create a correlation matrix
corr = iris.corr()
corr

# Create a correlation matrix corr = iris.corr() corr

Out[ ]:

	sepal_length	sepal_width	petal_length	petal_width
sepal_length	1.000000	-0.117570	0.871754	0.817941
sepal_width	-0.117570	1.000000	-0.428440	-0.366126
petal_length	0.871754	-0.428440	1.000000	0.962865
petal_width	0.817941	-0.366126	0.962865	1.000000

In [ ]:

# Create the heatmap
sns.heatmap(corr,  annot=True)

# Create the heatmap sns.heatmap(corr, annot=True)

Out[ ]:

<AxesSubplot:>

In [ ]:

import seaborn as sns
import pandas as pd

# Load the tips dataset
tips = sns.load_dataset("tips")

# Create a FacetGrid
g = sns.FacetGrid(tips, col="time", row="sex")

# Map the plot to the FacetGrid
g.map(sns.scatterplot, "total_bill", "tip")

import seaborn as sns import pandas as pd # Load the tips dataset tips = sns.load_dataset("tips") # Create a FacetGrid g = sns.FacetGrid(tips, col="time", row="sex") # Map the plot to the FacetGrid g.map(sns.scatterplot, "total_bill", "tip")

Out[ ]:

<seaborn.axisgrid.FacetGrid at 0x7f4660479ac0>

In [ ]:

import seaborn as sns
import matplotlib.pyplot as plt

# Set the plot background color
sns.set_style("darkgrid")

# Load the tips dataset
tips = sns.load_dataset("tips")

# Set the color palette
sns.set_palette("husl")

# Create a scatter plot
sns.scatterplot(data=tips, x="total_bill", y="tip", hue="sex", size="size")

# Set the title and axis labels
plt.title("Tips by Total Bill")
plt.xlabel("Total Bill")
plt.ylabel("Tip")

# Set the font size and style
sns.set(font_scale=1.5, font="Arial")

import seaborn as sns import matplotlib.pyplot as plt # Set the plot background color sns.set_style("darkgrid") # Load the tips dataset tips = sns.load_dataset("tips") # Set the color palette sns.set_palette("husl") # Create a scatter plot sns.scatterplot(data=tips, x="total_bill", y="tip", hue="sex", size="size") # Set the title and axis labels plt.title("Tips by Total Bill") plt.xlabel("Total Bill") plt.ylabel("Tip") # Set the font size and style sns.set(font_scale=1.5, font="Arial")

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