Seaborn tsplot : How to implement in Python with example?

Lets implement Seaborn tsplot () using matplotlib, numpy ,pandas and Seaborn modules. We can easily parameterize the dataframe in tsplot(). In this article, we will simply implement tsplot() with minimal data example.

Seaborn tsplot Implementation: Stepwise –

Let’s break this demonstration in three small steps.

Step 1: Import Seaborn –

In this step, we will simply import the seaborn python package. Because tsplot() function is a part/ member of this package.

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

We have also imported matplotlib to draw the complete plot and defining figsize. Remaining two (pandas and NumPy) are for data point creation.

Step 2: Data Creation –

tsplot needs some data for plotting. We will utilize NumPy and pandas for sample data creation.

#data creation for tsplot()
speed, time = np.meshgrid(np.arange(24), np.arange(1,3))
sample_dataFrame = pd.DataFrame({"speed": speed.flatten(), "time": time.flatten()})
sample_dataFrame["computed_param"] = np.random.randint(2,15, size=len(sample_dataFrame))

Basically, we have created a dataframe with three columns [speed, time, computed_param]. Let’s see the first few lines of this data frame.

print(sample_dataFrame.head())

Step 3: Using tsplot() function-

Once we have the data ready. All we need to invoke the tsplot().

plt.figure(figsize=(4,4))
sns.tsplot(sample_dataFrame, time='time', unit = "speed", condition='speed', value='computed_param')
plt.show()

We have written three statements in this section.

1. figsize parameterization is self-explanatory.
2. sns.tsplot() invoking the most important function. We have parameterized our dataFrame.
3. It is just to present/ show the figure.

Note –

if you are getting the error “AttributeError:module ‘seaborn’ has no attribute ‘tsplot’ “. Please downgrade your seaborn version. We have checked that version seaborn==0.9.0 is compatible with tsplot function. Hence we can downgrade it version seaborn==0.9.0. Use the below command for that.

pip install seaborn==0.9.0

It will install the previous version of seaborn and reinstall the new one.

Conclusion-

Seaborn Data Visualization Library in python is really quite impressive. In this article, We have seen how can we use seaborn tsplot(). I hope this stepwise implementation made you quite clear about this topic.

If you think, We left something and you want to contribute something more with it. Please comment in the comment box. We are always ready to help you.

Thanks

Data Science Learner Team