Plotting Basics with `MatPlotlib` and `Seaborn` - Answer Key

Authors

Noor Sohail

Will Gammerdinger

Published

March 15, 2026

Exercise 1

Add a plt.ylabel() layer to the current plot such that the y-axis is labeled “Mean expression”.

# Set the theme to "whitegrid"
sns.set_style(style = "whitegrid")

# Initialize a plot with a specific size
plt.figure(figsize=(8, 6))

# Add a scatterplot layer to the plot, coloring points by genotype
sns.scatterplot(data = new_metadata,
                x="age_in_days", 
                y="mean_expression",
                hue="genotype",
                style="celltype",
                s=50)

# Change the size and text of the axis label
plt.xlabel(xlabel = "Age in Days",
           fontsize=20)

# Add an plt.ylabel() layers to the current plot such that the y-axis is labeled “Mean expression”.
plt.ylabel(ylabel = "Mean expression",
           fontsize=20)
           
# Render the plot
plt.show()

Use the plt.title() layer to add a plot title of your choice.

# Set the theme to "whitegrid"
sns.set_style(style = "whitegrid")

# Initialize a plot with a specific size
plt.figure(figsize=(8, 6))

# Add a scatterplot layer to the plot, coloring points by genotype
sns.scatterplot(data = new_metadata,
                x="age_in_days", 
                y="mean_expression",
                hue="genotype",
                style="celltype",
                s=50)

# Change the size and text of the axis label
plt.xlabel(xlabel = "Age in Days",
           fontsize=20)

# Add an plt.ylabel() layers to the current plot such that the y-axis is labeled “Mean expression”.
plt.ylabel(ylabel = "Mean expression",
           fontsize=20)

# Use the plt.title() layer to add a plot title of your choice.
plt.title(label = "Mean expression by age")

# Render the plot
plt.show()

When you add the arguments loc="right" to the plt.title() function, what does it change?

# Set the theme to "whitegrid"
sns.set_style(style = "whitegrid")

# Initialize a plot with a specific size
plt.figure(figsize=(8, 6))

# Add a scatterplot layer to the plot, coloring points by genotype
sns.scatterplot(data = new_metadata,
                x="age_in_days", 
                y="mean_expression",
                hue="genotype",
                style="celltype",
                s=50)

# Change the size and text of the axis label
plt.xlabel(xlabel = "Age in Days",
           fontsize=20)

# Add an plt.ylabel() layers to the current plot such that the y-axis is labeled “Mean expression”.
plt.ylabel(ylabel = "Mean expression",
           fontsize=20)

# Use the plt.title() layer to add a plot title of your choice.
# When you add the arguments loc="right" to the plt.title() function, what does it change?
plt.title(label = "Mean expression by age",
          loc="right")

# Render the plot
plt.show()

The title of the plot is now right-aligned.

Try adding the layer plt.legend(loc="center right") to the end of your code. What does this do? How many layers can be added to a plot, in your estimation?

# Set the theme to "whitegrid"
sns.set_style(style = "whitegrid")

# Initialize a plot with a specific size
plt.figure(figsize=(8, 6))

# Add a scatterplot layer to the plot, coloring points by genotype
sns.scatterplot(data = new_metadata,
                x="age_in_days", 
                y="mean_expression",
                hue="genotype",
                style="celltype",
                s=50)

# Change the size and text of the axis label
plt.xlabel(xlabel = "Age in Days",
           fontsize=20)

# Add an plt.ylabel() layers to the current plot such that the y-axis is labeled “Mean expression”.
plt.ylabel(ylabel = "Mean expression",
           fontsize=20)

# Use the plt.title() layer to add a plot title of your choice.
plt.title(label = "Mean expression by age")

# Change legend location
plt.legend(loc="center right")

# Render the plot
plt.show()

plt.legend changes the location of the legend in the plot. We can add as many layers as we would like.

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--- title: "Plotting Basics with `MatPlotlib` and `Seaborn` - Answer Key" author: - Noor Sohail - Will Gammerdinger date: "2026-03-15" license: "CC-BY-4.0" editor_options: markdown: wrap: 72 jupyter: intro_python --- ```{python} #| label: load_libraries_data_py #| echo: false import matplotlib.pyplot as plt import seaborn as sns import pandas as pd # Load the new metadata data frame that we created in the previous lesson new_metadata = pd.read_csv("data/new_metadata.csv", index_col=0) ``` # Exercise 1 1. Add a `plt.ylabel()` layer to the current plot such that the y-axis is labeled "Mean expression". ```{python} #| label: exercise_1 # Set the theme to "whitegrid" sns.set_style(style = "whitegrid") # Initialize a plot with a specific size plt.figure(figsize=(8, 6)) # Add a scatterplot layer to the plot, coloring points by genotype sns.scatterplot(data = new_metadata, x="age_in_days", y="mean_expression", hue="genotype", style="celltype", s=50) # Change the size and text of the axis label plt.xlabel(xlabel = "Age in Days", fontsize=20) # Add an plt.ylabel() layers to the current plot such that the y-axis is labeled “Mean expression”. plt.ylabel(ylabel = "Mean expression", fontsize=20) # Render the plot plt.show() ``` 2. Use the `plt.title()` layer to add a plot title of your choice. ```{python} #| label: exercise_2 # Set the theme to "whitegrid" sns.set_style(style = "whitegrid") # Initialize a plot with a specific size plt.figure(figsize=(8, 6)) # Add a scatterplot layer to the plot, coloring points by genotype sns.scatterplot(data = new_metadata, x="age_in_days", y="mean_expression", hue="genotype", style="celltype", s=50) # Change the size and text of the axis label plt.xlabel(xlabel = "Age in Days", fontsize=20) # Add an plt.ylabel() layers to the current plot such that the y-axis is labeled “Mean expression”. plt.ylabel(ylabel = "Mean expression", fontsize=20) # Use the plt.title() layer to add a plot title of your choice. plt.title(label = "Mean expression by age") # Render the plot plt.show() ``` 3. When you add the arguments `loc="right"` to the `plt.title()` function, what does it change? ```{python} #| label: exercise_3 # Set the theme to "whitegrid" sns.set_style(style = "whitegrid") # Initialize a plot with a specific size plt.figure(figsize=(8, 6)) # Add a scatterplot layer to the plot, coloring points by genotype sns.scatterplot(data = new_metadata, x="age_in_days", y="mean_expression", hue="genotype", style="celltype", s=50) # Change the size and text of the axis label plt.xlabel(xlabel = "Age in Days", fontsize=20) # Add an plt.ylabel() layers to the current plot such that the y-axis is labeled “Mean expression”. plt.ylabel(ylabel = "Mean expression", fontsize=20) # Use the plt.title() layer to add a plot title of your choice. # When you add the arguments loc="right" to the plt.title() function, what does it change? plt.title(label = "Mean expression by age", loc="right") # Render the plot plt.show() ``` The title of the plot is now right-aligned. 4. Try adding the layer `plt.legend(loc="center right")` to the end of your code. What does this do? How many layers can be added to a plot, in your estimation? ```{python} #| label: exercise_4 # Set the theme to "whitegrid" sns.set_style(style = "whitegrid") # Initialize a plot with a specific size plt.figure(figsize=(8, 6)) # Add a scatterplot layer to the plot, coloring points by genotype sns.scatterplot(data = new_metadata, x="age_in_days", y="mean_expression", hue="genotype", style="celltype", s=50) # Change the size and text of the axis label plt.xlabel(xlabel = "Age in Days", fontsize=20) # Add an plt.ylabel() layers to the current plot such that the y-axis is labeled “Mean expression”. plt.ylabel(ylabel = "Mean expression", fontsize=20) # Use the plt.title() layer to add a plot title of your choice. plt.title(label = "Mean expression by age") # Change legend location plt.legend(loc="center right") # Render the plot plt.show() ``` `plt.legend` changes the location of the legend in the plot. We can add as many layers as we would like.