QuickDataScience | Quick & Easy Data Science

We have discussed Exploratory Data Analysis, known as EDA & have also seen few powerful libraries that we can use extensively for EDA. EDA is a key step in Machine Learning, as it provides the start point for our Machine Learning task. But, there are a lot of issues related to traditional Data Analysis techniques. There are too many new libraries coming up in the market to rectify these issues. One such API is AutoViz, which provides Quick and Easy visualization with some insights about the data.

Another day, another beautiful library for Exploratory Data Analysis(EDA) . Having studied some great libraries like Lux , D-tale , pandas profiling of EDA , we are back with another great API, 'SWEETVIZ', which you can use for your Data Science Project. Introduction It is an open-source Library of Python & is still in the development phase. It already has some great features to offer, & makes it our choice to bring it for you. Its sole purpose is to visualise & analyse data Quickly. The best feature of this API is it provides an option to compare two datasets, i.e. we can compare & analyse the test vs training data together. That's not all it's, just the starting. Let's dive deeper and see what it has more to offer us. 

Source: Google Images Pandas Profiling is an Open-Source Library of Python. It focuses on easing out the process of initial data analysis, by providing a tool to perform the analysis of our data Quick & Easy. It's also considered a major EDA library, creating visuals, graphs, data profiling reports, pandas reports within seconds, in just a line of code. It saves a lot of time, which is usually lost in visualizing & understanding the data. It extends the pandas data frame to create a report for Quick & Easy Data Analysis.

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 SQL? Structured Query Language is also known as SQL is the database language and is one of the most famous and in-demand technology.  This language was specially developed for database management i.e. creating a database, inserting and updating records in them, managing accesses and retrieving data from it. SQL is mostly used for Relational Database Management Systems.  Its demand is increasing every single day. As there is an increase in data, demand and need for SQL increases. It is been used by web developers, data analysts, data engineers, and in every other field where we need to store and retrieve data.  One of the main reasons why SQL is gaining popularity is that it is simple, easy, quick, and powerful. Another reason is that the most commonly used version of SQL(MySQL) is open-source(FREE) Another great feature of  SQL is Non Procedural language(explained in the next section). 

EDA EDA - Exploratory Data Analysis is the technique of defining, analyzing and investigate the dataset. This technique is used by most data scientists, engineers and everyone who is related to or wants to work and analyze the data. Saying that, it includes the whole majority of us as at any point of time we are dealing with data and we un-knowingly do an initial analysis about which in technical terms is referred to as   "Exploratory Data Analysis". Here is a formal definition of the EDA:-  In statistics, exploratory data analysis is an approach to analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods.  Still confused about how every one of using this process..!! Let me explain it with a simple example... Suppose you and your group plan for lunch in a restaurant... as soon as we hear "lunch" and "restaurant" our mind starts creating a list of all the known places, next as someon

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)