A lollipop plot is a hybrid between a and a . It shows the relationship between a numerical variable and another variable, numerical or categorical. It's better to decrease the order and represent horizontal lines.
First, Let's create a dataset.
# Create a dataset
df = pd.DataFrame({'group':list(map(chr, range(70, 90))), 'values':np.random.uniform(size=20)})
ordered_df = df.sort_values(by='values') # reorder it by 'values'
my_range=range(1,len(df.index)+1) # calcaulate data range
1. Univariate Lollipop
plt.style.use('dark_background') # set the figure style
plt.figure(figsize = (14,8)) # set the figure size
#create lollipop bar and lollipop head
plt.hlines(y=my_range, xmin=0, xmax=ordered_df['values'], color='skyblue')
plt.plot(ordered_df['values'], my_range, "o")
plt.yticks(my_range, ordered_df['group']) # reset yticks
plt.title("Lollipop Plot", loc='left') # set title and title location
plt.xlabel('Score')
plt.ylabel('Group')
2. Highlight Lollipop
Moreover, we .can add some eye-catching features for storytelling. For example, highlight a group that specifically interests you with a bigger size and different colors.
# Create a color if the group is "A"
A_color=np.where(ordered_df ['group']=='A', 'gold', 'skyblue')
A_size=np.where(ordered_df ['group']=='A', 100, 30)
plt.hlines(y=my_range, xmin=0, xmax=ordered_df['values'], color=my_color, linewidth =2)
plt.scatter(ordered_df['values'], my_range, color=A_color, s=A_size)
# Add title and axis names
plt.yticks(my_range, ordered_df['group'])
plt.title("Highlight A Lollipop", loc='left')
plt.xlabel('Score')
plt.ylabel('Group')
3. Multivariate Lollipop
We can use multi-variables lollipop if you have more than one observation for each group. Instead of displaying the values of both groups one beside each other, show them on the same line, and represent the difference.
Now we need to create a new dataset with two variables.
# create white color lollipop bar
plt.hlines(y=my_range, xmin=ordered_df['value1'], xmax=ordered_df['value2'], color='w',alpha = 0.6)
# create lollipop head1 in magnet color and set size =80
plt.scatter(ordered_df['value1'], my_range, color='m', s = 80,label='var 1',marker='^')
# create lollipop head2 in cyan color and set size = 100
plt.scatter(ordered_df['value2'], my_range, color='c',s = 100, label='var 2')
plt.legend() # show legend
# Add title and axis names
plt.yticks(my_range, ordered_df['group'])
plt.title("Multivariable Lollipop", loc='left')
plt.xlabel('Score')
plt.ylabel('Group')
