In order to avoid the creation of a spaghetti plot, it is a good practice to highlight the group(s) that interests you the most in your line plot. It allows the reader to understand your point quickly, instead of struggling to decipher hundreds of lines.
The trick is to plot all the groups with thin and discreet lines first. Then, replete the interesting group(s) with strong amdreally visible lines. Moreover, it is good practice to annotate this group with a custom annotation.
# libraries and data
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) })
#plt.style.use('fivethirtyeight')
plt.style.use('seaborn-darkgrid')
my_dpi=96
plt.figure(figsize=(480/my_dpi, 480/my_dpi), dpi=my_dpi)
# multiple line plot
for column in df.drop('x', axis=1):
plt.plot(df['x'], df[column], marker='', color='grey', linewidth=1, alpha=0.4)
# Now re do the interesting curve, but biger with distinct color
plt.plot(df['x'], df['y5'], marker='', color='orange', linewidth=4, alpha=0.7)
# Change xlim
plt.xlim(0,12)
# Let's annotate the plot
num=0
for i in df.values[9][1:]:
num+=1
name=list(df)[num]
if name != 'y5':
plt.text(10.2, i, name, horizontalalignment='left', size='small', color='grey')
# And add a special annotation for the group we are interested in
plt.text(10.2, df.y5.tail(1), 'Mr Orange', horizontalalignment='left', size='small', color='orange')
# Add titles
plt.title("Evolution of Mr Orange vs other students", loc='left', fontsize=12, fontweight=0, color='orange')
plt.xlabel("Time")
plt.ylabel("Score")
