Data Analysis of COVID-19
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Data Analysis of COVID-19

Project period

08/21/2020 - 08/31/2020

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Project Category

Computer Science



Data Analysis of COVID-19
Data Analysis of COVID-19

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.

Resources Required

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.

Download:
Project Code Code copy
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    "import numpy as np\n",
    "import datetime"
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       "           date  World  Afghanistan  Albania  Algeria  Andorra  Angola  \\\n",
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       "\n",
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       "\n",
       "     Vietnam  Western Sahara  Yemen  Zambia  Zimbabwe  \n",
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       "229      1.0             0.0    1.0     4.0       2.0  \n",
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       "231      1.0             0.0    5.0     4.0       3.0  \n",
       "\n",
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     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_cases = pd.read_csv('https://covid.ourworldindata.org/data/ecdc/total_cases.csv').fillna(0)\n",
    "total_deaths = pd.read_csv('https://covid.ourworldindata.org/data/ecdc/total_deaths.csv').fillna(0)\n",
    "new_cases = pd.read_csv('https://covid.ourworldindata.org/data/ecdc/new_cases.csv').fillna(0)\n",
    "new_deaths = pd.read_csv('https://covid.ourworldindata.org/data/ecdc/new_deaths.csv').fillna(0)\n",
    "\n",
    "spike=new_cases['China'].values.argmax()\n",
    "new_cases.iloc[spike]=new_cases.iloc[spike-1]\n",
    "\n",
    "#total_deaths.tail()\n",
    "new_deaths.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most deaths on 2020-08-09\n"
     ]
    },
    {
     "data": {
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       "          Region  Deaths\n",
       "0  United States  1069.0\n",
       "1         Brazil   905.0\n",
       "2          India   861.0\n",
       "3         Mexico   695.0\n",
       "4   South Africa   301.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_death_indecies=new_deaths.iloc[-1].values[2:].argsort()[-5:][::-1]\n",
    "regions=[]\n",
    "values=[]\n",
    "for i in max_death_indecies:\n",
    "    region=new_deaths.columns[i+2]\n",
    "    regions.append(region)\n",
    "    values.append(new_deaths[region].values[-1])\n",
    "    \n",
    "date=new_deaths.date.values[-1]\n",
    "print(f'Most deaths on {date}')\n",
    "d={'col1':[1,2], 'col2':[3,4]}\n",
    "pd.DataFrame(data={'Region': regions, 'Deaths': values})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "regions=['Germany', 'Italy', 'Brazil', 'India', 'United States', 'Japan', 'Sweden']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=new_cases.index\n",
    "for region in regions:\n",
    "    plt.plot(x,new_cases[region].values, label=region)\n",
    "plt.ylabel('New Cases')\n",
    "plt.xlabel('Days')\n",
    "plt.legend(loc='upper left')\n",
    "plt.title('New Cases')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=new_deaths.index\n",
    "for region in regions:\n",
    "    plt.plot(x,new_deaths[region].values, label=region)\n",
    "plt.ylabel('New Deaths')\n",
    "plt.xlabel('Days')\n",
    "plt.legend(loc='upper left')\n",
    "plt.title('New Deaths')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The fastest growing region is India,which is doubling every  23.3 days\n"
     ]
    }
   ],
   "source": [
    "dt=5\n",
    "regions=['Italy', 'United States', 'Germany', 'India', 'Japan', 'Sweden']\n",
    "r_d={}\n",
    "r_d_list=[]\n",
    "for region in regions:\n",
    "    n1=total_cases[region].values[-1]\n",
    "    n0=total_cases[region].values[-1-dt]\n",
    "    dn=(n1-n0)/n0\n",
    "    r=dt/(np.log2(dn+1))\n",
    "    r_d_list.append(r)\n",
    "    r_d[region]=r\n",
    "    \n",
    "y_pos=np.arange(len(regions))\n",
    "\n",
    "plt.bar(y_pos, r_d_list, align='center')\n",
    "plt.xticks(y_pos, regions)\n",
    "plt.title('Doubling Period in Days')\n",
    "plt.show()\n",
    "\n",
    "\n",
    "fastest_index=np.array(r_d_list).argmin()\n",
    "region=regions[fastest_index]\n",
    "if region[-1]=='s':\n",
    "    region='the'+region\n",
    "print('The fastest growing region is {region},which is doubling every {rate: .1f} days'. format(region=region, rate=r_d_list[fastest_index])) \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "t=np.array(range(7))\n",
    "start_date=datetime.datetime.strptime(date, '%Y-%m-%d')\n",
    "date_range=[(start_date+datetime.timedelta(days=int(d))).strftime('%Y-%m-%d') for d in t]\n",
    "\n",
    "for region in regions:\n",
    "    n_o=total_cases[region].values[-1]\n",
    "    n=np.around(n_o*np.exp2(t/r_d[region]))\n",
    "    plt.plot(t,n/1000, label=region)\n",
    "plt.ylabel('Thousands of People')\n",
    "plt.xlabel('Date')\n",
    "plt.xticks(t,date_range, rotation='vertical')\n",
    "plt.legend(loc='upper left')\n",
    "plt.title('Reported Infections')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Estimate of the number of days until symptoms/testing are reported\n",
    "\n",
    "lag=14\n",
    "\n",
    "t=np.array(range(7))\n",
    "start_date=datetime.datetime.strptime(date, '%Y-%m-%d')\n",
    "date_range=[(start_date+datetime.timedelta(days=int(d))).strftime('%Y-%m-%d') for d in t]\n",
    "\n",
    "for region in regions:\n",
    "    n_o=total_cases[region].values[-1]\n",
    "    n=np.around(n_o*np.exp2((t+lag)/r_d[region]))\n",
    "    plt.plot(t,n/1000, label=region)\n",
    "\n",
    "plt.ylabel('Thousands of People')\n",
    "plt.xlabel('Date')\n",
    "plt.xticks(t, date_range, rotation='vertical')\n",
    "plt.legend(loc='upper left')\n",
    "plt.title('Actual Infection Estimates')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mortality_rate=0.5/100\n",
    "infection_rate=1/mortality_rate\n",
    "\n",
    "x=total_deaths.index\n",
    "for region in regions:\n",
    "    plt.plot(x, infection_rate*total_deaths[region].values, label=region)\n",
    "\n",
    "plt.ylabel('Total Infections')\n",
    "plt.yscale('log')\n",
    "plt.xlabel('Days')\n",
    "plt.legend(loc='upper left')\n",
    "plt.title('Total Infections by Date')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "regions=['Germany', 'India','United States','Japan', 'South Korea', 'Italy','Brazil', 'Sweden']\n",
    "\n",
    "dt=5\n",
    "allRegions=total_cases.columns[1:]\n",
    "r_d_time={}\n",
    "for region in regions:\n",
    "    r_d_time[region]=[]\n",
    "    \n",
    "look_back=28\n",
    "for region in regions:\n",
    "    for i in range(-look_back,0):\n",
    "        \n",
    "        n1=total_cases[region].values[i]\n",
    "        n0=total_cases[region].values[i-dt]\n",
    "        dn=(n1-n0)/n0\n",
    "        r=dt/(np.log2(dn+1))\n",
    "        r_d_time[region].append(r)\n",
    "    \n",
    "regions=['India', 'United States', 'Brazil', 'Sweden']\n",
    "date_range=range(-look_back,0)\n",
    "for region in regions:\n",
    "    plt.plot(date_range, r_d_time[region], label=region)\n",
    "plt.ylabel('Doubling Period (days)')\n",
    "#plt.yscale('log')\n",
    "plt.xlabel('Date')\n",
    "plt.xticks(date_range, total_cases.date[-look_back:], rotation='vertical')\n",
    "plt.legend(loc='upper left')\n",
    "plt.title('Doubling Period over Time')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#regions=['Germany','Italy','Spain','India','United States','Japan','South Korea']\n",
    "\n",
    "regions=['Germany','India','United States','Japan','South Korea','Sweden']\n",
    "population={'Germany':83783942,'Italy':60461826, 'Spain':46754778,'India':1380004385,'United States':331002651,'Japan':1264476461, 'South Korea':51269185,'Sweden':10099265,'Brazil':212559417}\n",
    "\n",
    "current_deaths=total_deaths.iloc[-1]\n",
    "values=[]\n",
    "for region in regions:\n",
    "    values.append(1000000*current_deaths[region]/population[region])\n",
    "    \n",
    "y_pos=np.arange(len(regions))\n",
    "\n",
    "plt.bar(y_pos, values, align='center')\n",
    "plt.xticks(y_pos,regions, rotation='vertical')\n",
    "plt.ylabel('Deaths per Million')\n",
    "plt.title('Fraction of Deaths by Region')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "regions=['Germany', 'India','United States', 'Japan','South Korea','Italy','Brazil','Sweden']\n",
    "\n",
    "current_deaths=total_deaths.iloc[-1]\n",
    "infection_percent=[]\n",
    "for region in regions:\n",
    "    infection_percent.append(100*infection_rate*current_deaths[region]/population[region])\n",
    "    \n",
    "y_pos=np.arange(len(regions))\n",
    "\n",
    "plt.bar(y_pos, infection_percent, align='center')\n",
    "plt.xticks(y_pos,regions,rotation='vertical')\n",
    "plt.ylabel('Percentage of Population')\n",
    "plt.title('Infection Rate by Region')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Region</th>\n",
       "      <th>Doubling period (days)</th>\n",
       "      <th>Infection Rate(%)</th>\n",
       "      <th>Time to herd immunity (months)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>21.454842</td>\n",
       "      <td>9.454015</td>\n",
       "      <td>2.092460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>India</td>\n",
       "      <td>18.910344</td>\n",
       "      <td>0.628679</td>\n",
       "      <td>4.273851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>United States</td>\n",
       "      <td>53.458519</td>\n",
       "      <td>9.814121</td>\n",
       "      <td>5.119011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>69.660939</td>\n",
       "      <td>11.412712</td>\n",
       "      <td>6.172236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Germany</td>\n",
       "      <td>206.052517</td>\n",
       "      <td>2.195170</td>\n",
       "      <td>34.357007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>South Korea</td>\n",
       "      <td>177.873268</td>\n",
       "      <td>0.118980</td>\n",
       "      <td>54.235140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Italy</td>\n",
       "      <td>825.667869</td>\n",
       "      <td>11.644703</td>\n",
       "      <td>72.369913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Japan</td>\n",
       "      <td>213.860106</td>\n",
       "      <td>0.016434</td>\n",
       "      <td>85.274616</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Region  Doubling period (days)  Infection Rate(%)  \\\n",
       "6         Brazil               21.454842           9.454015   \n",
       "1          India               18.910344           0.628679   \n",
       "2  United States               53.458519           9.814121   \n",
       "7         Sweden               69.660939          11.412712   \n",
       "0        Germany              206.052517           2.195170   \n",
       "4    South Korea              177.873268           0.118980   \n",
       "5          Italy              825.667869          11.644703   \n",
       "3          Japan              213.860106           0.016434   \n",
       "\n",
       "   Time to herd immunity (months)  \n",
       "6                        2.092460  \n",
       "1                        4.273851  \n",
       "2                        5.119011  \n",
       "7                        6.172236  \n",
       "0                       34.357007  \n",
       "4                       54.235140  \n",
       "5                       72.369913  \n",
       "3                       85.274616  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Percentage of population toreach herd immunity\n",
    "herd_immunity=74\n",
    "t_herd=[]\n",
    "i=0\n",
    "rd_values=[]\n",
    "days_per_month=365.25/12\n",
    "for region in regions:\n",
    "    rd=r_d_time[region][-1]\n",
    "    rd_values.append(rd)\n",
    "    t_herd.append(rd*np.log2(herd_immunity/infection_percent[i])/days_per_month)\n",
    "    i +=1\n",
    "d={'Region':regions, 'Doubling period (days)': rd_values, 'Infection Rate(%)': infection_percent, 'Time to herd immunity (months)':t_herd} \n",
    "df=pd.DataFrame(data=d)\n",
    "df.sort_values(by='Time to herd immunity (months)')\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "regions=['Germany','India','United States','Japan','South Korea','Italy','Brazil','Sweden']\n",
    "deaths=total_deaths.iloc[-1][regions]\n",
    "cases=total_cases.iloc[-1][regions]\n",
    "rates=100*deaths/cases\n",
    "ax=rates.plot(kind='bar', title='Percentage of reported cases resulting in death')\n",
    "x_offset=-0.2\n",
    "y_offset=0.1\n",
    "for p in ax.patches:\n",
    "    b=p.get_bbox()\n",
    "    val=\"{:.1f}\".format(b.y1 + b.y0)\n",
    "    ax.annotate(val, ((b.x0+b.x1)/2+ x_offset, b.y1 + y_offset))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
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COVID19-Data-Analysis

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