Python Advanced- scatter plot with MatplotLib

Have you tried drawing your first pyplot? If not then please see my previous post about this.
Let's move ahead and learn about the matplotlib scatter plot

Before plotting a plot we need data to plot. So here we are taking an example of cars data in csv format which you can download here cars data
If you face any issue while downloading the file, comment me your email so that I can share the same directly.

Since the cars data is in csv format we need to first read the data with the help of pandas library as below-

The data will be looked look as below-

Since data is too long we need solid information from the data to plot so run Correlation & then run Covariance to find the most correlated variable to MPG-

Final cleaning of the cars data-

See now we have info to plot then let's plot it as given below-

Looks very cool right. Let's plot another one -

Key Note-Boxplots are great when you have a numeric column that you want to compare across different categories. When you want to visualize two numeric columns, scatter plots are ideal.

Please try above plotting in your notebook and comment if you face any issue.

Comments

Learn the fastest way to build data apps

Another post starts with you beautiful people! I hope you have enjoyed and learned something new from my previous three posts about machine learning model deployment. In one post we have learned How to deploy a model as FastAPI? I n the second post, we have learned How to deploy a deep learning model as RestAPI ? and in the third post, we have also learned How to scale your deep learning model API? If you are following my blog posts, you have seen how easily you have transit yourselves from aspiring to a mature data scientist. In this new post, I am going to share a new framework- Streamlit which will help you to easily create a beautiful app with Python only. I will show here how had I used the Streamlit framework to create an app for my YOLOv3 custom model. What is Streamlit? Streamlit’s open-source app framework is the easiest way for data scientists and machine learning engineers to create beautiful, performant apps in only a few hours!...

Exploring The File Import

Another post starts with you beautiful people! Today we will explore various file import options in Python which I learned from a great learning site- DataCamp . In order to import data into Python, we should first have an idea of what files are in our working directory. We will learn step by step examples as given below- Importing entire text files- In this exercise, we'll be working with the file mobydick.txt [ download here ] It is a text file that contains the opening sentences of Moby Dick, one of the great American novels! Here you'll get experience opening a text file, printing its contents to the shell and, finally, closing it- # Open a file: file file = open('mobydick.txt', mode='r') # Print it print(file.read()) # Check whether file is closed print(file.closed) # Close file file.close() # Check whether file is closed print(file.closed) Importing text files line by line- For large files, we may not want to print all of th...

Machine Learning-Cross Validation & ROC curve

Another post starts with you beautiful people! Hope you enjoyed my previous post about improving your model performance by confusion metrix . Today we will continue our performance improvement journey and will learn about Cross Validation (k-fold cross validation) & ROC in Machine Learning. A common practice in data science competitions is to iterate over various models to find a better performing model. However, it becomes difficult to distinguish whether this improvement in score is coming because we are capturing the relationship better or we are just over-fitting the data. To find the right answer of this question, we use cross validation technique. This method helps us to achieve more generalized relationships. What is Cross Validation? Cross Validation is a technique which involves reserving a particular sample of a data set on which we do not train the model. Later, we test the model on this sample before finalizing the model. Here are the steps involved in...

Learn Data Science using Python

Search This Blog