Bar plots in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a bar plot used for in data science?

A bar plot is used to show and compare the sizes or counts of different categories using rectangular bars. It helps us see which categories are bigger or smaller.

beginner

How do you create a simple vertical bar plot using pandas?

Use the plot.bar() method on a pandas DataFrame or Series. For example, data.plot.bar() will create a vertical bar plot.

beginner

What is the difference between plot.bar() and plot.barh() in pandas?

plot.bar() creates vertical bars, while plot.barh() creates horizontal bars. Use horizontal bars when category names are long or for better readability.

intermediate

How can you add labels to the x-axis and y-axis in a pandas bar plot?

After creating the plot, use plt.xlabel('label') and plt.ylabel('label') from matplotlib to add axis labels.

intermediate

Why might you use stacked bar plots and how do you create them in pandas?

Stacked bar plots show parts of categories stacked on top of each other to compare totals and parts. Use data.plot.bar(stacked=True) to create them.

Which pandas method creates a vertical bar plot?

A plot.bar()

B plot.barh()

C plot.line()

D plot.scatter()

The method plot.bar() creates vertical bar plots in pandas.

What parameter makes a bar plot stacked in pandas?

A stack=True

B orientation='horizontal'

C kind='stacked'

D stacked=True

Use stacked=True to create stacked bar plots in pandas.

Which plot type is best when category names are long?

A Horizontal bar plot

B Vertical bar plot

C Line plot

D Pie chart

Horizontal bar plots (plot.barh()) are better for long category names.

How do you add axis labels to a pandas bar plot?

A Using <code>data.label()</code>

B Using <code>plt.xlabel()</code> and <code>plt.ylabel()</code>

C Using <code>data.axis_labels()</code>

D Using <code>plot.labels()</code>

Axis labels are added with matplotlib functions plt.xlabel() and plt.ylabel().

What does a bar plot show?

A Relationship between two continuous variables

B Distribution of a single continuous variable

C Comparison of sizes or counts of categories

D Trend over time

Bar plots compare sizes or counts of different categories.

Explain how to create and customize a basic bar plot using pandas.

Think about the pandas plotting method and matplotlib labels.

Describe when and why you would use a horizontal bar plot instead of a vertical one.

Consider label length and plot orientation.