Exploring The File Import- Continue

Another post starts with you beautiful people!
I hope you have enjoyed my previous post about Exploring The File Import where we learned about flat file import.
But there are a number of datatypes that cannot be saved easily to flat files, such as lists and dictionaries.
In this exercise we will deal with Pickle,Excel,SAS and HDF5 files.

First we will see how to import the pickle file-
In this exercise, we'll import the pickle package, open a previously pickled data structure from a file and load it.You can find more details about pickle here-what is pickle?

Run the above code snippet in your notebook and discover what Python datatype it yields.

Second we see how to load a excel file-
Whether you like it or not, any working data scientist will need to deal with Excel spreadsheets at some point in time. You won't always want to do so in Excel, however!
Here, we'll learn how to use pandas to import Excel spreadsheets and how to list the names of the sheets in any loaded .xls file.
Specifically, we'll be loading and checking out the spreadsheet 'PRIO Battle Deaths Dataset 3.1.xls', modified from the Peace Research Institute Oslo's (PRIO) dataset.
This data contains age-adjusted mortality rates due to war in various countries over several years.

There may be more than 1 sheet in a xls file so in the below code snippet we learn how to read each sheet-

Third we will see how to load a SAS file and plot the data-
In this exercise, we'll figure out how to import a SAS file as a DataFrame using SAS7BDAT and pandas. Tell me more about sas7bdat

Result-

Next we will learn how to load a HDF5 file-
In this exercise, we'll import it using the h5py library [tell me more]. We'll also print out its datatype to confirm we have imported it correctly.You can find the LIGO data used in on Signal Processing plus loads of documentation and tutorials here-LIGO Dataset

Result-

Extracting data from your HDF5 file-
In this exercise, we'll extract some of the LIGO experiment's actual data from the HDF5 file and we'll visualize it. You can find more about this type of file here- What is HDF5?

Result-

How to load a MATLAB file-
In this exercise, we'll figure out how to load a MATLAB file using scipy.io.loadmat().

This file contains gene expression data from the Albeck Lab at UC Davis. You can find the data and some great documentation here-download dataset

Run the above code in your notebook and discover what Python datatype it yields.

Comments

How to use opencv-python with Darknet's YOLOv4?

Another post starts with you beautiful people 😊 Thank you all for messaging me your doubts about Darknet's YOLOv4. I am very happy to see in a very short amount of time my lovely aspiring data scientists have learned a state of the art object detection and recognition technique. If you are new to my blog and to computer vision then please check my following blog posts one by one- Setup Darknet's YOLOv4 Train custom dataset with YOLOv4 Create production-ready API of YOLOv4 model Create a web app for your YOLOv4 model Since now we have learned to use YOLOv4 built on Darknet's framework. In this post, I am going to share with you how can you use your trained YOLOv4 model with another awesome computer vision and machine learning software library- OpenCV and of course with Python 🐍. Yes, the Python wrapper of OpenCV library has just released it's latest version with support of YOLOv4 which you can install in your system using below command- pip install opencv-pyt...

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...

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...

Learn Data Science using Python

Search This Blog