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Today COVID-2019 is a worldwide threat to the living society. The whole world is putting much effort to fight against the spread of this deadly disease(Covid-19) in terms of finance, data sources, life-risk treatments, and several other resources. The many artificial intelligence researchers are focusing their expertise knowledge to develop models for analyzing this epidemic situation using nationwide shared data. We contribute towards the well-being of living society, this project proposes to utilize the machine learning models with the aim for understanding data and analyzed data along with the prediction of future reachability of the COVID-2019 across the World.
Data analysis could be a method of inspecting, cleansing, transforming, and analyzing data with the goal of discovering helpful information, informing conclusions, and supporting decision-making. In simple words, data analysis is the process of collecting and organizing data in order to draw helpful conclusions from it. The process of data analysis uses analytical and logical reasoning to gain information from the data.
Why: Problem statement
COVID-19 is spreading across the world. My neighbour was affected by coronavirus and he was kept in hospital for more than 20 days. He suffered a lot. He didn’t have awareness of the count of people who are suffering. Due to his carelessness, he was affected and left the family and took treatment. Not only my neighbor, many people are also affected. Inorder to give more awareness to the people, I decided to do this project.
I collected the affected people’s records from various places and sources. These records are used to predict the level of COVID-19 spreading to the various places. It is very difficult to predict the accurate result like how many people are affected on a daily basis. We could not manually calculate the number of people who are affected and the most affected states and countries. I decided to use Data analysis to update the current counts.
Coronavirus disease (COVID-19) is an inflammation disease from a new virus. Viral pandemics are a serious threat. Some of India’s big cities are facing the pandemic. Five cities Mumbai, Delhi, Chennai, Thane, and Ahmedabad account for half of all coronavirus cases and deaths. By using data analysis technology we can easily predict the result and reduce the work. And the result will be perfect too.
How: Solution description
To overcome this problem I find a better solution using Data Science. This analysis will help us to find the common analysis of the notions about the virus spread based on the dataset perspective. There is a lot of official and unofficial data sources on the internet providing COVID-19 related data. One of the most widely used datasets today is the one provided by the ourworldindata.org dataset.
COVID-19(Coronavirus) analysis is the process of analyzing the data to find the status of the coronavirus spread in the world. Based on that the customers can predict how far it spread and according to that, the customer can find the solution to overcome the threat.
In this project, I collected the raw Covid-19 dataset from the Kaggle website and processed the Data. After that I cleaned the dataset, In this cleaning process, I applied python programming to clean the data. Then I made exploratory data analyzed for the Covid-19 and visualized this analysis like scatter, plot, and line plot for better decision making. I used matplotlib library for the visualization process. Based on the analysis and visualization, I took better decision making for predicting COVID-19. The main advantage of this project is, we use live tracking to count the cases day by day.
This chart shows the percentage of deaths resulting in reported cases.
This chart shows how many deaths have occurred in the region.
How is it different from competition
Analysis of COVID-19 is a trending topic for this year. So everybody likes to use trending topics and as far as this deadly disease is spreading across the world this analysis is needed. As we use live data, it has current data which predict results accurately. We can see the counts regularly, because we are using the live tracking method. Our model predicts the count more accurately. We can see the number of counts, countries where the number counts increasing, and the states where the number counts increasing. We use data visualization techniques, in which the user can see the counts visually by graph. Graphing is easy to understand when compared to the normal data.
Who are your customers
The analysis of COVID-19(Coronavirus) data can be used by customers of the government to make better decisions. And also customers from different sectors can use this project like hospitals, government sectors, analysts, common people etc., where every sector and every individual needs to know about the status of coronavirus spread. This helps them to find out the good solution for this biggest threat and where we need to focus on much. This analytics will help them to find out the solution soon.
Project Phases and Schedule
Phase 1: Data collection - Data collection is the process of collecting or gathering data from various resources. In this project, I collected the covid-19 dataset from the ourworldindata.org website.
Phase 2: Data cleaning - Data cleaning is also known as data wrangling. Data wrangling is the process of transforming and mapping the data from one raw data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as data analytics.
Phase 3: Data Analysis - Data analysis is a process of transforming, and analyzing data to discover useful information for business decision making. The purpose of Data Analysis is to extract useful information from data and take the better decision based upon the data analysis.
Phase 4:Data Visualization - Data visualization is the graphical representation of information and easy to understand the users. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data. In this project, I mostly used line and bar charts to make better visualization using matplotlib.
Phase 5:Covid-19 Decision Making Report - Based on the analysis and visualization report I got the better decision making to predict COVID-19.
Anaconda tool - Anaconda may be a free and open-source distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale processing, prediction analysis, etc.), that aims to clarify package management and implementation. The distribution includes data-science packages appropriate for Windows, Linux, and macOS. You can download anaconda tool for Python by clicking this link https://anaconda.org/anaconda/python.
Python version 3.7 - Underneath the Python Releases for Windows find Latest Python 3 Release – Python 3.7. 4 (latest stable release as of now is Python 3.7. The advantages of Python 3.7 are Easier access to debuggers through a new breakpoint() built-in, Simple class creation using data classes, Customized access to module attributes, Improved support for type hinting and Higher precision timing functions. Most companies are still using Python 2 for legacy reasons, but more and more companies are using Python 3 or beginning to make the switch from 2 to 3.