Saturday, October 19, 2019

Python




   Python: Data Analytics!

 This blog is to focus on how to analyze data using Python and also to reach to the Data Science level. It includes concepts of Python from basic to intermediate level. All the concepts are explained with an example. It also has some real-life examples. Major examples will be updated soon, as currently, I am working on it. More topics will be updated as well. As mentioned, I will be updating some key techniques (advance) with Python programming for Data Science.
Feel free to comment and share your opinions.
Comment your doubts, I will try to clear them.
Happy Coding!!



Pandas: Pandas is a package which extracts data from CSV into DataFrame (will discuss in this blog) and allows us to do various things:
  • Calculate statistics and gives solutions about data e.g their mean, median, average, min, max and so on.
  • Cleans the data e.g removing missing values, removing duplicate values, filtering rows or columns with some data and so on.
  • Visualizes the data with the help of Matplotlib(discuss later) and plots data in pie chart, histogram, bubbles and more.
  • After cleaning the data, it stores and transformed data back into CSV or any other format.
Numpy: Numpy (Numeric Python) is also a package for scientific computing with Python. It is used to work with N-dimentsional array, Linear algebra, random number, Fourier Transform, etc.  It deals with multi-dimensional arrays and matrices. 




My Kaggle:
I have done analysis on a few data on Kaggle as well. Do check out and follow me ;)
PS: I just started :P
https://www.kaggle.com/heebahsaleem



My Publications:
Improved Image Steganography Algorithm using Huffman Code:
https://www.ijcaonline.org/archives/volume147/number12/25702-2016911242
[Foundation of Computer Science(FS), NY, USA, Volume 147 - Number 12, Tariq H, Saleem H]


My LinkedIn Profile:
https://www.linkedin.com/in/heebah-saleem-202615102/



More on Python will be updated soon on this page......... ;)
By the time, Happy coding :)

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