In this plot How to Create Strip Plot in Python. Previously we looked at Heatmap in Python Seaborn Library. That chart was handy for the population based charts and the charts which make use of the area and the specific points in the heatmap where it shows the points for the plot. In that context you I'd say that this new strip chart is also worth trying out. So check earlier tutorial for the heatmap.
Strip plot can be really good for visualizing the observations within your data set and you would be able to get the representation of the underlying distribution. This is something you can check out as we plot the strip chart. A lot of the current tutorial is based on fundamental. I think I make sure to get the simple dataset here for you. Like making use of the titanic dataset would be worth making use of for most of the scenarios.
So the titanic dataset is something you can check out for you in the github. Find here and download. The point is that you have to read this chart and also you can use this in the data and experiment with variety of the color palette, legend and other configuration parameter for the chart too.
And I have created a video to give you an overview on How to Create Strip Plot in Python using Seaborn. You should give this below video a look.
First thing you have to check if you have the python version. So you can check that out with the python commands.
python --version
And now we would be checking out the library install command too.
pip install numpy pandas jupyter seaborn matplotlib
Now let's take a look at how to open the jupyter notebook command.
jupyter notebook
Use the below commands to load the library.
import seaborn as sns
import matplotlib.pyplot as plt
Use the below code for loading the dataset.
titanic=sns.load_dataset("titanic")
titanic.head()
Here we have the data for the plotting and now you can plot the strip chart.
sns.stripplot(x="age", y="who", hue="alive",data=titanic)
plt.show()
Check the code below for complete reference.
import seaborn as sns
import matplotlib.pyplot as plt
titanic=sns.load_dataset("titanic")
titanic.head()
sns.stripplot(x="age", y="who", hue="alive",data=titanic)
plt.show()
For the image reference you can check out the code.
Next thing now that we have the jupyter python notebook open. I am going to add the command that would run the code and also show the plot image below the code. So you can check the plot image below. Here we are just hitting the run button so no need to push for the command.
As you can see the plot above. There are lot of things that you can do here. Like say you can add the oritnetation from horizontal to vertical. You can change the color, add groups for the data points, add legend and also add variety of the points that you can use with the plot chart. This is one thing you would love as you experiment there. I have noticed that plot by group is something you should definitely check out.
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