QuickDataScience | Quick & Easy Data Science

  Hope you are following up with us and by now you have become familiar with Jupyter Notebook , the basics of NLTK and Python functions .  Now, we will explore some more complex topics in NLTK, starting with statistics we will go through the loops and then learn how to apply conditions to the texts.  From the previous article, we know how to find the size of text, and how to access tokens based on indexes. But how to find out which tokens are highly repeated in the text or are there any specific tokens that the author has repeated many times to focus or emphasize on a particular topic.  Yes, this is very simple and can be done easily by using frequency distribution. Frequency Distribution can be understood simply as counting the repetition of different tokens in a text. Eg. In this paragraph, we have tokens ' frequency ', ' distribution ', and ' can ' present twice while 'understood', 'counting', 'repetition', 'using' etc have ju

We had a look over the basics of EDA in our previous article  EDA - Exploratory Data Analysis . So now let's move ahead and look at how we can automate the process and the various APIs used for the same. We will be focusing on the 7 major libraries that can be used for the same. These are our personal favourites & we prefer to use them most of the time.  We will look into the libraries' & will cover the install, load, and analyse parts for each separately.  D-tale Pandas - Profiling Lux Sweetviz Autoviz ExploriPy Dora

D-Tale is a new recently launched(Feb 2020) tool for Exploratory Data Analysis. It is made up of Flask(for back-end) and React(for Front-end) providing a powerful analysing and visualizing tool.  D-Tale is a Graphical User Interface platform that is not only Quick & Easy to understand but also great fun to use. It comes with so many features packed and loaded in it that reduces the manual work of Data Engineers/Scientists analysing and understanding the data and removes the load of looking for multiple different libraries used in EDA.  Let's have a look at some features which make it so amazing:- 1. Seamless Integration -- D-tale provides seamless integration with multiple python/ipython notebooks and terminals. So, we can use it with almost any IDE of our choice. 2. Friendly UI  -- The Graphical User Interface provided by D-tale is quite simple and easy to understand, such that anybody can easily get friendly with it & start working right away.  3. Support of multiple Py

What is Data Visualization?  Data Visualization as the name suggests is creating nice, beautiful and informative visuals from our data, which helps get more insights from the data. It helps us and the third person who sees our analysis or report in reading it better. Creating a good visualization helps us in understanding the data better and helps in our machine learning journey.  The data visualization process uses various graphs, graphics, plots for explaining the data and getting insights. DV is important to simplify complex data by making it more  accessible, understandable, and usable to its end users. If you want to know in more detail about data visualization you can Read IT Here .

  Image taken from Google images An easy to go guide for installing the Anaconda in Windows 10. 1. Prerequisites      Hardware Requirement * RAM — Min. 8GB, if you have SSD in your system then 4GB RAM would also work. * CPU — Min. Quad-core, with at least 1.80GHz  Operating System * Windows 8 or later  System Architecture Windows- 64-bit x86, 32-bit x86  Space Minimum 5 GB disk space to download and install   Anaconda   We need to download the Anaconda from HERE .  On opening the link we would be greeted by a great web page.   Now click on "Get Started"   to continue...  The next step is to click on "Download Installer" to proceed...  Select the correct version based on your System's architecture. I will be using a 64-bit installer (477 MB). Your download should now.. it will take some time...  Let's catch up in 2nd Section (Unzip and Install)