Small multiples for line chart


Let’s say you want to build a line chart with several lines, one for each group of your dataset. Adding all of them on the same plot can quickly lead to a spaghetti plot, and thus provide a chart that is hard to read and gives few insights about the data. This post shows how to avoid it by creating several subplots using matplotlib.

Several ways exist to avoid creating a spaghetti plot, and one of them is using small multiple: here we cut the window in several subplots, one per group. Then, you can choose to display every group discretely, or not to show them at all. Note that you can easily do the same with the area chart.

Left graph

You can create multiple plots on the same figure by using the subplot() function of matplotlib.

Note that you can check this post to see more examples of the subplot() function.

# libraries
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
 
# Make a data frame
df=pd.DataFrame({'x': range(1,11), 'y1': np.random.randn(10), 'y2': np.random.randn(10)+range(1,11), 'y3': np.random.randn(10)+range(11,21), 'y4': np.random.randn(10)+range(6,16), 'y5': np.random.randn(10)+range(4,14)+(0,0,0,0,0,0,0,-3,-8,-6), 'y6': np.random.randn(10)+range(2,12), 'y7': np.random.randn(10)+range(5,15), 'y8': np.random.randn(10)+range(4,14), 'y9': np.random.randn(10)+range(4,14) })
 
# Initialize the figure style
plt.style.use('seaborn-darkgrid')
 
# create a color palette
palette = plt.get_cmap('Set1')
 
# multiple line plot
num=0
for column in df.drop('x', axis=1):
    num+=1
 
    # Find the right spot on the plot
    plt.subplot(3,3, num)
 
    # Plot the lineplot
    plt.plot(df['x'], df[column], marker='', color=palette(num), linewidth=1.9, alpha=0.9, label=column)
 
    # Same limits for every chart
    plt.xlim(0,10)
    plt.ylim(-2,22)
 
    # Not ticks everywhere
    if num in range(7) :
        plt.tick_params(labelbottom='off')
    if num not in [1,4,7] :
        plt.tick_params(labelleft='off')
 
    # Add title
    plt.title(column, loc='left', fontsize=12, fontweight=0, color=palette(num) )

# general title
plt.suptitle("How the 9 students improved\nthese past few days?", fontsize=13, fontweight=0, color='black', style='italic', y=1.02)
 
# Axis titles
plt.text(0.5, 0.02, 'Time', ha='center', va='center')
plt.text(0.06, 0.5, 'Note', ha='center', va='center', rotation='vertical')

# Show the graph
plt.show()

Right graph

As an alternative to the previous example, you can make multiple subplots consisting the lines of all groups with only one group highlighted in each subplot.

# libraries
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
 
# Make a data frame
df=pd.DataFrame({'x': range(1,11), 'y1': np.random.randn(10), 'y2': np.random.randn(10)+range(1,11), 'y3': np.random.randn(10)+range(11,21), 'y4': np.random.randn(10)+range(6,16), 'y5': np.random.randn(10)+range(4,14)+(0,0,0,0,0,0,0,-3,-8,-6), 'y6': np.random.randn(10)+range(2,12), 'y7': np.random.randn(10)+range(5,15), 'y8': np.random.randn(10)+range(4,14), 'y9': np.random.randn(10)+range(4,14) })
 
# Initialize the figure style
plt.style.use('seaborn-darkgrid')
 
# create a color palette
palette = plt.get_cmap('Set1')
 
# multiple line plot
num=0
for column in df.drop('x', axis=1):
    num+=1
 
    # Find the right spot on the plot
    plt.subplot(3,3, num)
 
    # plot every group, but discrete
    for v in df.drop('x', axis=1):
        plt.plot(df['x'], df[v], marker='', color='grey', linewidth=0.6, alpha=0.3)
 
    # Plot the lineplot
    plt.plot(df['x'], df[column], marker='', color=palette(num), linewidth=2.4, alpha=0.9, label=column)
 
    # Same limits for every chart
    plt.xlim(0,10)
    plt.ylim(-2,22)
 
    # Not ticks everywhere
    if num in range(7) :
        plt.tick_params(labelbottom='off')
    if num not in [1,4,7] :
        plt.tick_params(labelleft='off')
 
    # Add title
    plt.title(column, loc='left', fontsize=12, fontweight=0, color=palette(num) )

# general title
plt.suptitle("How the 9 students improved\nthese past few days?", fontsize=13, fontweight=0, color='black', style='italic', y=1.02)
 
# Axis titles
plt.text(0.5, 0.02, 'Time', ha='center', va='center')
plt.text(0.06, 0.5, 'Note', ha='center', va='center', rotation='vertical')

# Show the graph
plt.show()

Line chart

Area chart

Stacked Area

Streamgraph

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