Skip to main content

Python Advanced- pyplot with Matplotlib

Another post starts with you beautiful people and today we will learn about Matplotlib library.
Matplotlib is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.
For more details about this library please visit here matplotlib library

Let's starts with plotting a pyplot for the example of stock I have given in my previous page of DataFrame. If you haven't seen that post please go to the side bar of the blog at right top most corner and see Python Advanced- DataFrame.

For a quick view I have a stock price data where I have done some cleaning as below-


Now I want to compute 10 days moving average of the stock data-

Next we need to import the required library as below-

Here %matplotlib inline displays our plot after every line of code.

Now it's time make a plot for our stock data-

See how a beautiful plot is prepared with some simple pyplot methods.
Labels:

Comments

Post a Comment

Popular posts from this blog

How to convert your YOLOv4 weights to TensorFlow 2.2.0?

Another post starts with you beautiful people! Thank you all for your overwhelming response in my last two posts about the YOLOv4. It is quite clear that my beloved aspiring data scientists are very much curious to learn state of the art computer vision technique but they were not able to achieve that due to the lack of proper guidance. Now they have learnt exact steps to use a state of the art object detection and recognition technique from my last two posts. If you are new to my blog and want to use YOLOv4 in your project then please follow below two links- How to install and compile Darknet code with GPU? How to train your custom data with YOLOv4? In my  last post we have trained our custom dataset to identify eight types of Indian classical dance forms. After the model training we have got the YOLOv4 specific weights file as 'yolo-obj_final.weights'. This YOLOv4 specific weight file cannot be used directly to either with OpenCV or with TensorFlow currently becau...
92 comments
Read more

How to deploy your ML model as Fast API?

Another post starts with you beautiful people! Thank you all for showing so much interests in my last posts about object detection and recognition using YOLOv4. I was very happy to see many aspiring data scientists have learnt from my past three posts about using YOLOv4. Today I am going to share you all a new skill to learn. Most of you have seen my post about  deploying and consuming ML models as Flask API   where we have learnt to deploy and consume a keras model with Flask API  . In this post you are going to learn a new framework-  FastAPI to deploy your model as Rest API. After completing this post you will have a new industry standard skill. What is FastAPI? FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. It is easy to learn, fast to code and ready for production . Yes, you heard it right! Flask is not meant to be used in production but with FastAPI you can use you...
50 comments
Read more

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!...
49 comments
Read more