Libraries
First, we need to load a few libraries:
- matplotlib: for creating/styling the plot
- seaborn: for creating the plot
numpyfor data generation
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as npBasic Lineplot
You can create a basic line chart with the plot() function of matplotlib library. If you give only a serie of values, matplotlib will consider that these values are ordered and will use values from 1 to n to create the X axis (figure 1):
# create data
values=np.cumsum(np.random.randn(1000,1))
# use the plot function
plt.plot(values)
# show the graph
plt.show()
Seaborn Customization
For a more trendy look, you can use the set_theme() function of seaborn library. You will automatically get the look of figure 2.
sns.set_theme()
# create data
values=np.cumsum(np.random.randn(1000,1))
# use the plot function
plt.plot(values)
# show the graph
plt.show()
Use lineplot with unordered data
You can also make a line chart from 2 series of values (X and Y axis). However, make sure that your X axis values are ordered! If not, you will get this kind of figure (figure 3).
# import the iris dataset
df = sns.load_dataset('iris')
# plot
plt.plot( 'sepal_width', 'sepal_length', data=df)
# show the graph
plt.show()
Use lineplot with ordered data
If your X data is ordered, then you will get a similar figure as figure 1:
import pandas as pd
df=pd.DataFrame({'xvalues': range(1,101), 'yvalues': np.random.randn(100) })
# plot
plt.plot( 'xvalues', 'yvalues', data=df)
# show the graph
plt.show()
Going further
This post explains how to customize a line plot with matplotlib and seaborn libraries.
You might be interested in how to use 2 different y axis for 2 lines and how to have a log scale.
