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 install and compile YOLO v4 with GPU enable settings in Windows 10?

Another post starts with you beautiful people! Last year I had shared a post about  installing and compiling Darknet YOLOv3   in your Windows machine and also how to detect an object using  YOLOv3 with Keras . This year on April' 2020 the fourth generation of YOLO has arrived and since then I was curious to use this as soon as possible. Due to my project (built on YOLOv3 :)) work I could not find a chance to check this latest release. Today I got some relief and successfully able to install and compile YOLOv4 in my machine. In this post I am going to share a single shot way to do the same in your Windows 10 machine. If your machine does not have GPU then you can follow my  previous post  by just replacing YOLOv3 related files with YOLOv4 files. For GPU having Windows machine, follow my steps to avoid any issue while building the Darknet repository. My machine has following configurations: Windows 10 64 bit Intel Core i7 16 GB RAM NVIDIA GeForce G...
46 comments
Read more

How to CORRECTLY convert Darknet/Yolov4 weights to TFLite format?

  Greetings, computer vision practitioners👮! I hope you're all doing well in your projects. Recently, I received a new requirement from a client regarding an object detection solution that had been successfully deployed as a REST API. The solution was seamlessly integrated into both web and mobile applications. However, the client encountered network reliability issues, particularly in rural areas where poor connectivity occasionally caused the solution to fail on mobile devices💔. As we know, network disruptions are a common challenge, but they become critical when they impact business operations. My client sought a robust solution to address this issue, ensuring uninterrupted functionality regardless of network conditions. In this blog post, we will explore how I tackled this challenge and implemented an effective solution💓. The Solution: Enabling Offline Object Detection for Mobile Devices Given that network connectivity issues are beyond our control, the most effective soluti...
11 comments
Read more

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...
27 comments
Read more