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Introduction to Data Visualization with Matplotlib

Run the hidden code cell below to import the data used in this course.

1 hidden cell

Introduction to Matplotlib

Using the matplotlib.pyplot interface

# Import the matplotlib.pyplot submodule and name it plt
import matplotlib.pyplot as plt

# Create a Figure and an Axes with plt.subplots
fig, ax = plt.subplots()

# Call the show function to show the result
plt.show()

Adding data to an Axes object

# Import the matplotlib.pyplot submodule and name it plt
import matplotlib.pyplot as plt

# Create a Figure and an Axes with plt.subplots
fig, ax = plt.subplots()

# Plot MLY-PRCP-NORMAL from seattle_weather against the MONTH
ax.plot(seattle_weather["MONTH"], seattle_weather["MLY-PRCP-NORMAL"])

# Plot MLY-PRCP-NORMAL from austin_weather against MONTH
ax.plot(austin_weather["MONTH"],austin_weather["MLY-PRCP-NORMAL"])

# Call the show function
plt.show()

Customizing data appearance

# Plot Seattle data, setting data appearance
ax.plot(seattle_weather["MONTH"], seattle_weather["MLY-PRCP-NORMAL"],color="b",marker="o",linestyle="--")

# Plot Austin data, setting data appearance
ax.plot(austin_weather["MONTH"], austin_weather["MLY-PRCP-NORMAL"], color="r",marker="v",linestyle="--")

# Call show to display the resulting plot
plt.show()

Customizing axis labels and adding titles

ax.plot(seattle_weather["MONTH"], seattle_weather["MLY-PRCP-NORMAL"])
ax.plot(austin_weather["MONTH"], austin_weather["MLY-PRCP-NORMAL"])

# Customize the x-axis label
ax.set_xlabel("Time (months)")

# Customize the y-axis label
ax.set_ylabel("Precipitation (inches)")

# Add the title
ax.set_title("Weather patterns in Austin and Seattle")

# Display the figure
plt.show()

Creating small multiples with plt.subplots

# Create a Figure and an array of subplots with 2 rows and 2 columns
fig, ax = plt.subplots(2, 2)

# Addressing the top left Axes as index 0, 0, plot month and Seattle precipitation
ax[0,0].plot(seattle_weather["MONTH"], seattle_weather["MLY-PRCP-NORMAL"])

# In the top right (index 0,1), plot month and Seattle temperatures
ax[0,1].plot(seattle_weather["MONTH"], seattle_weather["MLY-TAVG-NORMAL"])

# In the bottom left (1, 0) plot month and Austin precipitations
ax[1,0].plot(austin_weather["MONTH"], austin_weather["MLY-PRCP-NORMAL"])

# In the bottom right (1, 1) plot month and Austin temperatures
ax[1,1].plot(austin_weather["MONTH"], austin_weather["MLY-TAVG-NORMAL"])
plt.show()

Small multiples with shared y axis

# Create a figure and an array of axes: 2 rows, 1 column with shared y axis
fig, ax = plt.subplots(2, 1, sharey=True)

# Plot Seattle precipitation data in the top axes
ax[0].plot(seattle_weather["MONTH"], seattle_weather["MLY-PRCP-NORMAL"], color = 'b')
ax[0].plot(seattle_weather["MONTH"], seattle_weather["MLY-PRCP-25PCTL"], color = 'b', linestyle = '--')
ax[0].plot(seattle_weather["MONTH"], seattle_weather["MLY-PRCP-75PCTL"], color = 'b', linestyle = '--')

# Plot Austin precipitation data in the bottom axes
ax[1].plot(austin_weather["MONTH"], austin_weather["MLY-PRCP-NORMAL"], color = 'r')
ax[1].plot(austin_weather["MONTH"], austin_weather["MLY-PRCP-25PCTL"], color = 'r', linestyle = '--')
ax[1].plot(austin_weather["MONTH"], austin_weather["MLY-PRCP-75PCTL"], color = 'r', linestyle = '--')

plt.show()
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