My Experiences in Python Programming Language

Getting Started with Medical Image Processing in Python Analyzing medical image in python is also possible. The source of medical image can come from X-Rays, MRI, CT and other.   X-Ray is the oldest medical imaging technique used to examine most area of the body to detect bone fracture and breaks. MRI stands for magnetic resonance imaging which produce slice images of the inside of the body like brain, cord, bones etc… CT stands for computational tomography or CAT computational axial tomography can scan the body and produce   detailed images of   internal organs, blood vessels and bones.  To be able to open a saved MRI image, X-Ray image or CT image, you might need some procedure because they are binary images which means is not possible to open them as text directly.  When a medical image scanner scans any organ of the body can send it to the workstation and produce a dcm image format   The format of medical image is mostly in dcm format. To open it ...

  Analyzing text file with pandas and numpy >>> import pandas as pd >>> import numpy as np >>> # Analyzing text file with pandas and numpy def fan(filename):          fl = open(filename, encoding = 'utf-8')          rfl = fl.read()          sfl = rfl.split()          sen_fl = rfl.splitlines()          fdist = [i for i in Counter(rfl.split()).most_common(10)]          print(fdist, file = open('newnew.txt', 'a+', encoding = 'utf-8'))          for w in sen_fl:                  harf = [i for i in Counter(w.replace(' ', '')).most_common()]       ...

Extract frequencies of a specific string or word on every chapter in one book or word within different books Surprisingly I decided to keep analyzing two different sentences in a one text or different texts or whatever sources books etc… for tomorrow.          Today as it might to be 23 Mai 2020 on COVID-19 period somewhere downtown in Senegal, I will try to show you how to extract the frequencies of a specific strings or words in every chapter. Assume that you have almost thousands of books there in a folder called for example books, and I would like to know the frequency of different drives of verb think or whatever in all those books. We can assume that those books are mostly talking about cars business. Let’s stigmatize the python here to get some reflects, here we go for the animation, I better call it luring python:   >>> source = ‘ ‘   # I can also call it as usually path = ‘ ‘ in the case I’m working in different...