#-------------------------------------------------------------------------------
# Importing Libraries
#-------------------------------------------------------------------------------
library(tidyverse)
## -- Attaching packages -------------------------------------------------------- tidyverse 1.3.0 --
## v ggplot2 3.3.1 v purrr 0.3.4
## v tibble 3.0.1 v dplyr 0.8.5
## v tidyr 1.1.0 v stringr 1.4.0
## v readr 1.3.1 v forcats 0.5.0
## -- Conflicts ----------------------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(lubridate) # for date handling
##
## Attaching package: 'lubridate'
## The following objects are masked from 'package:dplyr':
##
## intersect, setdiff, union
## The following objects are masked from 'package:base':
##
## date, intersect, setdiff, union
list.files(path = 'C:/Users/Rewati/Documents/R/COVID_19/')
## [1] "covid_19_data.csv"
## [2] "covid_19_data_old.csv"
## [3] "COVID19_line_list_data.csv"
## [4] "COVID19_open_line_list.csv"
## [5] "time_series_covid_19_confirmed.csv"
## [6] "time_series_covid_19_confirmed_US.csv"
## [7] "time_series_covid_19_deaths.csv"
## [8] "time_series_covid_19_deaths_US.csv"
## [9] "time_series_covid_19_recovered.csv"
#-------------------------------------------------------------------------------
# Load File for covid_19_data.
#-------------------------------------------------------------------------------
#df <- read.csv("C:/Users/Rewati/Documents/R/COVID_19/covid_19_data.csv")
df <- read.csv("C:/Users/Rewati/Documents/R/COVID_19/covid_19_data_old.csv")
str(df)
## 'data.frame': 57572 obs. of 8 variables:
## $ SNo : int 1 2 3 4 5 6 7 8 9 10 ...
## $ ObservationDate: chr "01/22/2020" "01/22/2020" "01/22/2020" "01/22/2020" ...
## $ Province.State : chr "Anhui" "Beijing" "Chongqing" "Fujian" ...
## $ Country.Region : chr "Mainland China" "Mainland China" "Mainland China" "Mainland China" ...
## $ Last.Update : chr "1/22/2020 17:00" "1/22/2020 17:00" "1/22/2020 17:00" "1/22/2020 17:00" ...
## $ Confirmed : num 1 14 6 1 0 26 2 1 4 1 ...
## $ Deaths : num 0 0 0 0 0 0 0 0 0 0 ...
## $ Recovered : num 0 0 0 0 0 0 0 0 0 0 ...
head(df)
## SNo ObservationDate Province.State Country.Region Last.Update Confirmed
## 1 1 01/22/2020 Anhui Mainland China 1/22/2020 17:00 1
## 2 2 01/22/2020 Beijing Mainland China 1/22/2020 17:00 14
## 3 3 01/22/2020 Chongqing Mainland China 1/22/2020 17:00 6
## 4 4 01/22/2020 Fujian Mainland China 1/22/2020 17:00 1
## 5 5 01/22/2020 Gansu Mainland China 1/22/2020 17:00 0
## 6 6 01/22/2020 Guangdong Mainland China 1/22/2020 17:00 26
## Deaths Recovered
## 1 0 0
## 2 0 0
## 3 0 0
## 4 0 0
## 5 0 0
## 6 0 0
names(df)
## [1] "SNo" "ObservationDate" "Province.State" "Country.Region"
## [5] "Last.Update" "Confirmed" "Deaths" "Recovered"
sum(df$Confirmed)
## [1] 520698929
sum(df$Recovered)
## [1] 221820396
sum(df$Deaths)
## [1] 30091353
df1 <- data.frame(state=c("Confirmed","Recovered","Deaths"),
cases=c(sum(df$Confirmed),sum(df$Recovered),sum(df$Deaths)))
ggplot(data=df1, aes(x=state, y=cases)) +
geom_bar(stat="identity", fill="steelblue")+
geom_text(aes(label=cases), vjust=-0.3, size=3.5)+
theme_minimal()
ggplot(data=df1, aes(x=state, y=cases, fill=state)) +
geom_bar(stat="identity")+
geom_text(aes(label=cases), vjust=1.5, size=3.5)+
theme_minimal()
# convert dates
df$Date <- as.Date(df$ObservationDate, format = '%m/%d/%y')
df$ObservationDate <- NULL
df$Last.Update <- NULL
df <- dplyr::group_by(df, Date) %>% dplyr::summarize(n=n(),
Confirmed=sum(Confirmed),
Deaths=sum(Deaths),
Recovered=sum(Recovered))
n <- nrow(df)
print(paste0('Observations: ', n))
## [1] "Observations: 166"
#-------------------------------------------------------------------------------
# Add few more features in data
#-------------------------------------------------------------------------------
df$Active <- df$Confirmed - df$Recovered - df$Deaths
df$MortRate <- df$Deaths / df$Confirmed
df$RecoRate <- df$Recovered / df$Confirmed
df$Reco_vs_Mort <- df$Recovered / df$Deaths
df$DiffConf <- 0
df$DiffConf[2:nrow(df)] <- diff(df$Confirmed)
df$RelIncrease <- c(NaN, df$DiffConf[2:n] / df$Confirmed[1:n-1])
df$DoublingDays <- round(log(2)/log(1+df$RelIncrease),2)
df$DiffDeath <- 0
df$DiffDeath[2:nrow(df)] <- diff(df$Deaths)
df$RelIncD <- c(NaN, df$DiffDeath[2:n] / df$Deaths[1:n-1])
df$DoublingDaysD <- round(log(2)/log(1+df$RelIncD),2)
# show data frame
head(df)
## # A tibble: 6 x 15
## Date n Confirmed Deaths Recovered Active MortRate RecoRate
## <date> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2020-01-22 38 555 17 28 510 0.0306 0.0505
## 2 2020-01-23 46 653 18 30 605 0.0276 0.0459
## 3 2020-01-24 41 941 26 36 879 0.0276 0.0383
## 4 2020-01-25 44 1438 42 39 1357 0.0292 0.0271
## 5 2020-01-26 47 2118 56 52 2010 0.0264 0.0246
## 6 2020-01-27 51 2927 82 61 2784 0.0280 0.0208
## # ... with 7 more variables: Reco_vs_Mort <dbl>, DiffConf <dbl>,
## # RelIncrease <dbl>, DoublingDays <dbl>, DiffDeath <dbl>, RelIncD <dbl>,
## # DoublingDaysD <dbl>
#-------------------------------------------------------------------------------
# Plotting Graphs for Analysis.
#-------------------------------------------------------------------------------
plot(df$Date, df$Confirmed, main = 'Confirmed Cases', type = 'b')
grid()
plot(df$Date, log10(df$Confirmed), main = 'Confirmed Cases -Log Scale', type = 'b')
grid()
plot(df$Date, df$DiffConf, main='Absolute Increase of Confirmed Cases', type='b')
grid()
plot(df$Date, df$RelIncrease, main='Relative Change vs Previous Day', type='b', ylim=c(0,0.1))
grid()
plot(df$Date, df$DoublingDays, main='Confirmed - Theoretical days until next doubling', type='b', ylim=c(0,1000))
grid()
plot(df$Date, df$Deaths, main='Deaths', type='b')
grid()
plot(df$Date, log10(df$Deaths), main='Deaths - Log Scale', type='b')
grid()
plot(df$Date, df$DiffDeath, main='Absolute Increase of Deaths', type='b')
grid()
plot(df$Date, df$RelIncD, main='Deaths - Relative Change vs Previous Day', type='b', ylim=c(0,0.05))
grid()
plot(df$Date, df$Recovered, main='Recovered', type='b')
grid()
plot(df$Date, df$Active, main='Active', type='b')
grid()
plot(df$Date, df$RecoRate, pch=16, col='darkgreen', type='b', ylab='Recovery Ratio', main='Recovery Ratio')
grid()
plot(df$Date, df$MortRate, pch=16, col='red', type='b', ylab='Death Ratio', main='Death Ratio')
grid()
plot(df$Date, df$Reco_vs_Mort, pch=16, col='blue', type='b', ylab='Recovered : Deaths', main='Recovered : Deaths')
grid()
# bubble plot (death ratio, recovery ratio, total positive cases)
ggplot(df, aes(x=RecoRate, y=MortRate, size=Confirmed, color=Date)) +
geom_point(alpha=0.7) + ggtitle('Ratios') + theme(legend.position="bottom")
write.csv(df, file='WorldData.csv')
#-------------------------------------------------------------------------------
# Filter data only for INDIA
#-------------------------------------------------------------------------------
#df <- read.csv("C:/Users/Rewati/Documents/R/COVID_19/covid_19_data.csv")
df <- read.csv("C:/Users/Rewati/Documents/R/COVID_19/covid_19_data_old.csv")
df_IND <- dplyr::filter(df, Country.Region == 'India')
df_IND
## SNo ObservationDate Province.State
## 1 431 01/30/2020
## 2 492 01/31/2020
## 3 548 02/01/2020
## 4 608 02/02/2020
## 5 673 02/03/2020
## 6 741 02/04/2020
## 7 811 02/05/2020
## 8 882 02/06/2020
## 9 955 02/07/2020
## 10 1027 02/08/2020
## 11 1099 02/09/2020
## 12 1172 02/10/2020
## 13 1244 02/11/2020
## 14 1317 02/12/2020
## 15 1390 02/13/2020
## 16 1464 02/14/2020
## 17 1539 02/15/2020
## 18 1614 02/16/2020
## 19 1689 02/17/2020
## 20 1764 02/18/2020
## 21 1839 02/19/2020
## 22 1916 02/20/2020
## 23 1996 02/21/2020
## 24 2080 02/22/2020
## 25 2164 02/23/2020
## 26 2249 02/24/2020
## 27 2342 02/25/2020
## 28 2439 02/26/2020
## 29 2544 02/27/2020
## 30 2651 02/28/2020
## 31 2772 02/29/2020
## 32 2896 03/01/2020
## 33 3017 03/02/2020
## 34 3163 03/03/2020
## 35 3289 03/04/2020
## 36 3452 03/05/2020
## 37 3625 03/06/2020
## 38 3826 03/07/2020
## 39 4052 03/08/2020
## 40 4309 03/09/2020
## 41 4574 03/10/2020
## 42 4782 03/11/2020
## 43 4997 03/12/2020
## 44 5278 03/13/2020
## 45 5452 03/14/2020
## 46 5700 03/15/2020
## 47 5968 03/16/2020
## 48 6237 03/17/2020
## 49 6515 03/18/2020
## 50 6801 03/19/2020
## 51 7092 03/20/2020
## 52 7383 03/21/2020
## 53 7686 03/22/2020
## 54 7984 03/23/2020
## 55 8279 03/24/2020
## 56 8579 03/25/2020
## 57 8881 03/26/2020
## 58 9188 03/27/2020
## 59 9495 03/28/2020
## 60 9806 03/29/2020
## 61 10118 03/30/2020
## 62 10431 03/31/2020
## 63 10744 04/01/2020
## 64 11057 04/02/2020
## 65 11372 04/03/2020
## 66 11687 04/04/2020
## 67 12003 04/05/2020
## 68 12322 04/06/2020
## 69 12642 04/07/2020
## 70 12962 04/08/2020
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## 81 16484 04/19/2020
## 82 16804 04/20/2020
## 83 17124 04/21/2020
## 84 17444 04/22/2020
## 85 17763 04/23/2020
## 86 18083 04/24/2020
## 87 18402 04/25/2020
## 88 18721 04/26/2020
## 89 19040 04/27/2020
## 90 19361 04/28/2020
## 91 19682 04/29/2020
## 92 20004 04/30/2020
## 93 20327 05/01/2020
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## 95 20973 05/03/2020
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## 113 27239 05/21/2020
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## 116 28595 05/24/2020
## 117 29047 05/25/2020
## 118 29499 05/26/2020
## 119 29951 05/27/2020
## 120 30402 05/28/2020
## 121 30955 05/29/2020
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## 124 32619 06/01/2020
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## 132 38010 06/09/2020
## 133 38812 06/10/2020 Andaman and Nicobar Islands
## 134 38813 06/10/2020 Andhra Pradesh
## 135 38829 06/10/2020 Arunachal Pradesh
## 136 38830 06/10/2020 Assam
## 137 38852 06/10/2020 Bihar
## 138 38885 06/10/2020 Chandigarh
## 139 38892 06/10/2020 Chhattisgarh
## 140 38911 06/10/2020 Dadar Nagar Haveli
## 141 38915 06/10/2020 Delhi
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## 143 38959 06/10/2020 Gujarat
## 144 38964 06/10/2020 Haryana
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## 146 38996 06/10/2020 Jammu and Kashmir
## 147 38999 06/10/2020 Jharkhand
## 148 39017 06/10/2020 Karnataka
## 149 39020 06/10/2020 Kerala
## 150 39045 06/10/2020 Ladakh
## 151 39061 06/10/2020 Madhya Pradesh
## 152 39067 06/10/2020 Maharashtra
## 153 39069 06/10/2020 Manipur
## 154 39082 06/10/2020 Meghalaya
## 155 39096 06/10/2020 Mizoram
## 156 39108 06/10/2020 Nagaland
## 157 39147 06/10/2020 Odisha
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## 159 39184 06/10/2020 Punjab
## 160 39194 06/10/2020 Rajasthan
## 161 39240 06/10/2020 Sikkim
## 162 39261 06/10/2020 Tamil Nadu
## 163 39265 06/10/2020 Telangana
## 164 39282 06/10/2020 Tripura
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## 166 39302 06/10/2020 Uttar Pradesh
## 167 39303 06/10/2020 Uttarakhand
## 168 39328 06/10/2020 West Bengal
## 169 39536 06/11/2020 Andaman and Nicobar Islands
## 170 39537 06/11/2020 Andhra Pradesh
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## 172 39554 06/11/2020 Assam
## 173 39576 06/11/2020 Bihar
## 174 39609 06/11/2020 Chandigarh
## 175 39616 06/11/2020 Chhattisgarh
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## 177 39639 06/11/2020 Delhi
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## 199 39992 06/11/2020 Telangana
## 200 40009 06/11/2020 Tripura
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## 204 40057 06/11/2020 West Bengal
## 205 40265 06/12/2020 Andaman and Nicobar Islands
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## 227 40550 06/12/2020 Mizoram
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## 232 40649 06/12/2020 Rajasthan
## 233 40696 06/12/2020 Sikkim
## 234 40717 06/12/2020 Tamil Nadu
## 235 40721 06/12/2020 Telangana
## 236 40738 06/12/2020 Tripura
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## 238 40759 06/12/2020 Uttar Pradesh
## 239 40760 06/12/2020 Uttarakhand
## 240 40786 06/12/2020 West Bengal
## 241 40994 06/13/2020 Andaman and Nicobar Islands
## 242 40995 06/13/2020 Andhra Pradesh
## 243 41011 06/13/2020 Arunachal Pradesh
## 244 41012 06/13/2020 Assam
## 245 41034 06/13/2020 Bihar
## 246 41067 06/13/2020 Chandigarh
## 247 41074 06/13/2020 Chhattisgarh
## 248 41093 06/13/2020 Dadra and Nagar Haveli and Daman and Diu
## 249 41097 06/13/2020 Delhi
## 250 41127 06/13/2020 Goa
## 251 41142 06/13/2020 Gujarat
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## 253 41154 06/13/2020 Himachal Pradesh
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## 264 41291 06/13/2020 Nagaland
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## 270 41446 06/13/2020 Tamil Nadu
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## 274 41488 06/13/2020 Uttar Pradesh
## 275 41489 06/13/2020 Uttarakhand
## 276 41515 06/13/2020 West Bengal
## 277 41723 06/14/2020 Andaman and Nicobar Islands
## 278 41724 06/14/2020 Andhra Pradesh
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## 282 41796 06/14/2020 Chandigarh
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## 307 42179 06/14/2020 Telangana
## 308 42196 06/14/2020 Tripura
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## 310 42217 06/14/2020 Uttar Pradesh
## 311 42218 06/14/2020 Uttarakhand
## 312 42244 06/14/2020 West Bengal
## 313 42452 06/15/2020 Andaman and Nicobar Islands
## 314 42453 06/15/2020 Andhra Pradesh
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## 343 42908 06/15/2020 Telangana
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## 347 42947 06/15/2020 Uttarakhand
## 348 42973 06/15/2020 West Bengal
## 349 43181 06/16/2020 Andaman and Nicobar Islands
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## 357 43284 06/16/2020 Delhi
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## 378 43633 06/16/2020 Tamil Nadu
## 379 43637 06/16/2020 Telangana
## 380 43654 06/16/2020 Tripura
## 381 43668 06/16/2020 Unknown
## 382 43675 06/16/2020 Uttar Pradesh
## 383 43676 06/16/2020 Uttarakhand
## 384 43702 06/16/2020 West Bengal
## 385 43910 06/17/2020 Andaman and Nicobar Islands
## 386 43911 06/17/2020 Andhra Pradesh
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## 393 44013 06/17/2020 Delhi
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## 407 44195 06/17/2020 Mizoram
## 408 44207 06/17/2020 Nagaland
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## 963 55591 07/03/2020 Arunachal Pradesh
## 964 55592 07/03/2020 Assam
## 965 55614 07/03/2020 Bihar
## 966 55647 07/03/2020 Chandigarh
## 967 55654 07/03/2020 Chhattisgarh
## 968 55673 07/03/2020 Dadra and Nagar Haveli and Daman and Diu
## 969 55677 07/03/2020 Delhi
## 970 55707 07/03/2020 Goa
## 971 55722 07/03/2020 Gujarat
## 972 55727 07/03/2020 Haryana
## 973 55734 07/03/2020 Himachal Pradesh
## 974 55759 07/03/2020 Jammu and Kashmir
## 975 55762 07/03/2020 Jharkhand
## 976 55780 07/03/2020 Karnataka
## 977 55783 07/03/2020 Kerala
## 978 55808 07/03/2020 Ladakh
## 979 55824 07/03/2020 Madhya Pradesh
## 980 55830 07/03/2020 Maharashtra
## 981 55832 07/03/2020 Manipur
## 982 55845 07/03/2020 Meghalaya
## 983 55859 07/03/2020 Mizoram
## 984 55871 07/03/2020 Nagaland
## 985 55911 07/03/2020 Odisha
## 986 55944 07/03/2020 Puducherry
## 987 55948 07/03/2020 Punjab
## 988 55958 07/03/2020 Rajasthan
## 989 56005 07/03/2020 Sikkim
## 990 56026 07/03/2020 Tamil Nadu
## 991 56030 07/03/2020 Telangana
## 992 56047 07/03/2020 Tripura
## 993 56061 07/03/2020 Unknown
## 994 56068 07/03/2020 Uttar Pradesh
## 995 56069 07/03/2020 Uttarakhand
## 996 56095 07/03/2020 West Bengal
## 997 56303 07/04/2020 Andaman and Nicobar Islands
## 998 56304 07/04/2020 Andhra Pradesh
## 999 56320 07/04/2020 Arunachal Pradesh
## 1000 56321 07/04/2020 Assam
## 1001 56343 07/04/2020 Bihar
## 1002 56376 07/04/2020 Chandigarh
## 1003 56383 07/04/2020 Chhattisgarh
## 1004 56402 07/04/2020 Dadra and Nagar Haveli and Daman and Diu
## 1005 56406 07/04/2020 Delhi
## 1006 56436 07/04/2020 Goa
## 1007 56451 07/04/2020 Gujarat
## 1008 56456 07/04/2020 Haryana
## 1009 56463 07/04/2020 Himachal Pradesh
## 1010 56488 07/04/2020 Jammu and Kashmir
## 1011 56491 07/04/2020 Jharkhand
## 1012 56509 07/04/2020 Karnataka
## 1013 56512 07/04/2020 Kerala
## 1014 56537 07/04/2020 Ladakh
## 1015 56553 07/04/2020 Madhya Pradesh
## 1016 56559 07/04/2020 Maharashtra
## 1017 56561 07/04/2020 Manipur
## 1018 56574 07/04/2020 Meghalaya
## 1019 56588 07/04/2020 Mizoram
## 1020 56600 07/04/2020 Nagaland
## 1021 56640 07/04/2020 Odisha
## 1022 56673 07/04/2020 Puducherry
## 1023 56677 07/04/2020 Punjab
## 1024 56687 07/04/2020 Rajasthan
## 1025 56734 07/04/2020 Sikkim
## 1026 56755 07/04/2020 Tamil Nadu
## 1027 56759 07/04/2020 Telangana
## 1028 56776 07/04/2020 Tripura
## 1029 56790 07/04/2020 Unknown
## 1030 56797 07/04/2020 Uttar Pradesh
## 1031 56798 07/04/2020 Uttarakhand
## 1032 56824 07/04/2020 West Bengal
## 1033 57032 07/05/2020 Andaman and Nicobar Islands
## 1034 57033 07/05/2020 Andhra Pradesh
## 1035 57049 07/05/2020 Arunachal Pradesh
## 1036 57050 07/05/2020 Assam
## 1037 57072 07/05/2020 Bihar
## 1038 57105 07/05/2020 Chandigarh
## 1039 57112 07/05/2020 Chhattisgarh
## 1040 57131 07/05/2020 Dadra and Nagar Haveli and Daman and Diu
## 1041 57135 07/05/2020 Delhi
## 1042 57165 07/05/2020 Goa
## 1043 57180 07/05/2020 Gujarat
## 1044 57185 07/05/2020 Haryana
## 1045 57192 07/05/2020 Himachal Pradesh
## 1046 57217 07/05/2020 Jammu and Kashmir
## 1047 57220 07/05/2020 Jharkhand
## 1048 57238 07/05/2020 Karnataka
## 1049 57241 07/05/2020 Kerala
## 1050 57266 07/05/2020 Ladakh
## 1051 57282 07/05/2020 Madhya Pradesh
## 1052 57288 07/05/2020 Maharashtra
## 1053 57290 07/05/2020 Manipur
## 1054 57303 07/05/2020 Meghalaya
## 1055 57317 07/05/2020 Mizoram
## 1056 57329 07/05/2020 Nagaland
## 1057 57369 07/05/2020 Odisha
## 1058 57402 07/05/2020 Puducherry
## 1059 57406 07/05/2020 Punjab
## 1060 57416 07/05/2020 Rajasthan
## 1061 57463 07/05/2020 Sikkim
## 1062 57484 07/05/2020 Tamil Nadu
## 1063 57488 07/05/2020 Telangana
## 1064 57505 07/05/2020 Tripura
## 1065 57519 07/05/2020 Unknown
## 1066 57526 07/05/2020 Uttar Pradesh
## 1067 57527 07/05/2020 Uttarakhand
## 1068 57553 07/05/2020 West Bengal
## Country.Region Last.Update Confirmed Deaths Recovered
## 1 India 1/30/20 16:00 1 0 0
## 2 India 1/31/2020 23:59 1 0 0
## 3 India 1/31/2020 8:15 1 0 0
## 4 India 2020-02-02T06:03:08 2 0 0
## 5 India 2020-02-03T21:43:02 3 0 0
## 6 India 2020-02-03T21:43:02 3 0 0
## 7 India 2020-02-03T21:43:02 3 0 0
## 8 India 2020-02-03T21:43:02 3 0 0
## 9 India 2020-02-03T21:43:02 3 0 0
## 10 India 2020-02-03T21:43:02 3 0 0
## 11 India 2020-02-03T21:43:02 3 0 0
## 12 India 2020-02-03T21:43:02 3 0 0
## 13 India 2020-02-03T21:43:02 3 0 0
## 14 India 2020-02-03T21:43:02 3 0 0
## 15 India 2020-02-13T18:53:02 3 0 0
## 16 India 2020-02-13T18:53:02 3 0 0
## 17 India 2020-02-13T18:53:02 3 0 0
## 18 India 2020-02-16T07:43:02 3 0 3
## 19 India 2020-02-16T07:43:02 3 0 3
## 20 India 2020-02-16T07:43:02 3 0 3
## 21 India 2020-02-16T07:43:02 3 0 3
## 22 India 2020-02-16T07:43:02 3 0 3
## 23 India 2020-02-16T07:43:02 3 0 3
## 24 India 2020-02-16T07:43:02 3 0 3
## 25 India 2020-02-16T07:43:02 3 0 3
## 26 India 2020-02-16T07:43:02 3 0 3
## 27 India 2020-02-16T07:43:02 3 0 3
## 28 India 2020-02-16T07:43:02 3 0 3
## 29 India 2020-02-16T07:43:02 3 0 3
## 30 India 2020-02-16T07:43:02 3 0 3
## 31 India 2020-02-16T07:43:02 3 0 3
## 32 India 2020-02-16T07:43:02 3 0 3
## 33 India 2020-03-02T22:33:09 5 0 3
## 34 India 2020-03-02T22:33:09 5 0 3
## 35 India 2020-03-04T12:33:03 28 0 3
## 36 India 2020-03-05T13:53:03 30 0 3
## 37 India 2020-03-06T13:03:12 31 0 3
## 38 India 2020-03-07T18:13:27 34 0 3
## 39 India 2020-03-08T09:23:05 39 0 3
## 40 India 2020-03-09T09:13:17 43 0 3
## 41 India 2020-03-10T10:13:28 56 0 4
## 42 India 2020-03-11T22:13:12 62 1 4
## 43 India 2020-03-12T08:33:13 73 1 4
## 44 India 2020-03-11T20:00:00 82 2 4
## 45 India 2020-03-14T20:33:03 102 2 4
## 46 India 2020-03-15T18:20:18 113 2 13
## 47 India 2020-03-16T14:38:45 119 2 13
## 48 India 2020-03-17T15:33:06 142 3 14
## 49 India 2020-03-18T13:33:12 156 3 14
## 50 India 2020-03-19T20:43:02 194 4 15
## 51 India 2020-03-20T15:13:21 244 5 20
## 52 India 2020-03-21T17:43:03 330 4 23
## 53 India 3/8/20 5:31 396 7 24
## 54 India 2020-03-23 23:23:20 499 10 34
## 55 India 2020-03-24 23:41:50 536 10 40
## 56 India 2020-03-25 23:37:49 657 12 43
## 57 India 2020-03-26 23:53:24 727 20 45
## 58 India 2020-03-27 23:27:48 887 20 73
## 59 India 3/8/20 5:31 987 24 84
## 60 India 3/8/20 5:31 1024 27 95
## 61 India 3/8/20 5:31 1251 32 102
## 62 India 2020-03-31 23:49:27 1397 35 123
## 63 India 2020-04-01 22:04:58 1998 58 148
## 64 India 4/2/20 8:53 2543 72 191
## 65 India 2020-04-03 22:52:45 2567 72 192
## 66 India 4/4/20 9:38 3082 86 229
## 67 India 2020-04-05 23:13:44 3588 99 229
## 68 India 4/6/20 9:37 4778 136 375
## 69 India 2020-04-07 23:11:31 5311 150 421
## 70 India 2020-04-08 22:59:00 5916 178 506
## 71 India 2020-04-09 23:09:19 6725 226 620
## 72 India 2020-04-10 23:01:43 7598 246 774
## 73 India 2020-04-11 22:52:46 8446 288 969
## 74 India 2020-04-12 23:25:00 9205 331 1080
## 75 India 2020-04-13 23:15:42 10453 358 1181
## 76 India 2020-04-14 23:41:11 11487 393 1359
## 77 India 2020-04-15 23:04:26 12322 405 1432
## 78 India 2020-04-16 23:38:19 13430 448 1768
## 79 India 2020-04-17 23:38:48 14352 486 2041
## 80 India 2020-04-18 22:40:18 15722 521 2463
## 81 India 2020-04-19 23:49:05 17615 559 2854
## 82 India 2020-04-20 23:44:50 18539 592 3273
## 83 India 2020-04-21 23:39:09 20080 645 3975
## 84 India 2020-04-22 23:38:57 21370 681 4370
## 85 India 2020-04-24 03:31:35 23077 721 5012
## 86 India 2020-04-25 06:31:19 24530 780 5498
## 87 India 2020-04-26 02:31:18 26283 825 5939
## 88 India 2020-04-27 02:31:20 27890 881 6523
## 89 India 2020-04-28 02:31:20 29451 939 7137
## 90 India 2020-04-29 02:32:29 31324 1008 7747
## 91 India 2020-04-30 02:32:27 33062 1079 8437
## 92 India 2020-05-01 02:32:28 34863 1154 9068
## 93 India 2020-05-02 02:32:27 37257 1223 10007
## 94 India 2020-05-03 02:32:28 39699 1323 10819
## 95 India 2020-05-04 02:32:28 42505 1391 11775
## 96 India 2020-05-05 02:32:34 46437 1566 12847
## 97 India 2020-05-06 02:32:31 49400 1693 14142
## 98 India 2020-05-07 02:32:28 52987 1785 15331
## 99 India 2020-05-08 02:32:32 56351 1889 16776
## 100 India 2020-05-09 02:32:35 59695 1985 17887
## 101 India 2020-05-10 02:32:30 62808 2101 19301
## 102 India 2020-05-11 02:32:30 67161 2212 20969
## 103 India 2020-05-12 03:32:27 70768 2294 22549
## 104 India 2020-05-13 03:32:26 74292 2415 24420
## 105 India 2020-05-14 03:32:28 78055 2551 26400
## 106 India 2020-05-15 02:33:02 81997 2649 27969
## 107 India 2020-05-16 02:32:19 85784 2753 30258
## 108 India 2020-05-17 02:32:32 90648 2871 34224
## 109 India 2020-05-18 02:32:21 95698 3025 36795
## 110 India 2020-05-19 02:32:18 100328 3156 39233
## 111 India 2020-05-20 02:32:19 106475 3302 42309
## 112 India 2020-05-21 02:32:48 112028 3434 45422
## 113 India 2020-05-22 02:36:51 118226 3584 48553
## 114 India 2020-05-23 02:32:42 124794 3726 51824
## 115 India 2020-05-24 02:32:43 131423 3868 54385
## 116 India 2020-05-25 02:32:44 138536 4024 57692
## 117 India 2020-05-26 02:32:35 144950 4172 60706
## 118 India 2020-05-27 02:32:31 150793 4344 64277
## 119 India 2020-05-28 02:32:31 158086 4534 67749
## 120 India 2020-05-29 02:32:50 165386 4711 70920
## 121 India 2020-05-30 02:32:48 173491 4980 82627
## 122 India 2020-05-31 02:32:45 181827 5185 86936
## 123 India 2020-06-01 02:32:46 190609 5408 91852
## 124 India 2020-06-02 02:33:08 198370 5608 95754
## 125 India 2020-06-03 02:33:13 207191 5829 100285
## 126 India 2020-06-04 02:33:14 216824 6088 104071
## 127 India 2020-06-05 02:33:06 226713 6363 108450
## 128 India 2020-06-06 02:33:00 236184 6649 113233
## 129 India 2020-06-07 03:53:30 246622 6946 118695
## 130 India 2020-06-08 03:33:22 257486 7207 123848
## 131 India 2020-06-09 03:33:03 265928 7473 129095
## 132 India 2020-06-10 04:07:00 276146 7750 134670
## 133 India 2020-06-11 03:33:41 33 0 33
## 134 India 2020-06-11 03:33:41 5070 77 2802
## 135 India 2020-06-11 03:33:41 57 0 1
## 136 India 2020-06-11 03:33:41 2937 4 1085
## 137 India 2020-06-11 03:33:41 5459 32 2864
## 138 India 2020-06-11 03:33:41 323 5 286
## 139 India 2020-06-11 03:33:41 1240 6 386
## 140 India 2020-06-11 03:33:41 22 0 2
## 141 India 2020-06-11 03:33:41 31309 905 11861
## 142 India 2020-06-11 03:33:41 359 0 67
## 143 India 2020-06-11 03:33:41 21014 1313 14365
## 144 India 2020-06-11 03:33:41 5209 45 2134
## 145 India 2020-06-11 03:33:41 445 5 249
## 146 India 2020-06-11 03:33:41 4346 48 1506
## 147 India 2020-06-11 03:33:41 1411 8 559
## 148 India 2020-06-11 03:33:41 5921 66 2604
## 149 India 2020-06-11 03:33:41 2096 16 848
## 150 India 2020-06-11 03:33:41 108 1 52
## 151 India 2020-06-11 03:33:41 9849 420 6729
## 152 India 2020-06-11 03:33:41 90787 3289 42638
## 153 India 2020-06-11 03:33:41 304 0 61
## 154 India 2020-06-11 03:33:41 43 1 13
## 155 India 2020-06-11 03:33:41 88 0 1
## 156 India 2020-06-11 03:33:41 127 0 10
## 157 India 2020-06-11 03:33:41 3140 9 2133
## 158 India 2020-06-11 03:33:41 127 0 52
## 159 India 2020-06-11 03:33:41 2719 55 2167
## 160 India 2020-06-11 03:33:41 11245 255 8328
## 161 India 2020-06-11 03:33:41 13 0 0
## 162 India 2020-06-11 03:33:41 34914 307 18325
## 163 India 2020-06-11 03:33:41 3920 148 1809
## 164 India 2020-06-11 03:33:41 864 1 192
## 165 India 2020-06-11 03:33:41 9227 0 0
## 166 India 2020-06-11 03:33:41 11335 301 6669
## 167 India 2020-06-11 03:33:41 1537 13 755
## 168 India 2020-06-11 03:33:41 8985 415 3620
## 169 India 2020-06-12 05:09:52 38 0 33
## 170 India 2020-06-12 05:09:52 5429 80 3048
## 171 India 2020-06-12 05:09:52 61 0 4
## 172 India 2020-06-12 05:09:52 3319 6 1432
## 173 India 2020-06-12 05:09:52 5983 36 3266
## 174 India 2020-06-12 05:09:52 332 5 286
## 175 India 2020-06-12 05:09:52 1398 6 447
## 176 India 2020-06-12 05:09:52 30 0 2
## 177 India 2020-06-12 05:09:52 34687 1085 12731
## 178 India 2020-06-12 05:09:52 417 0 67
## 179 India 2020-06-12 05:09:52 22032 1385 15101
## 180 India 2020-06-12 05:09:52 5968 64 2260
## 181 India 2020-06-12 05:09:52 470 6 280
## 182 India 2020-06-12 05:09:52 4574 52 1820
## 183 India 2020-06-12 05:09:52 1599 8 630
## 184 India 2020-06-12 05:09:52 6245 72 2977
## 185 India 2020-06-12 05:09:52 2244 18 968
## 186 India 2020-06-12 05:09:52 135 1 54
## 187 India 2020-06-12 05:09:52 10241 431 7042
## 188 India 2020-06-12 05:09:52 97648 3590 46078
## 189 India 2020-06-12 05:09:52 366 0 73
## 190 India 2020-06-12 05:09:52 44 1 18
## 191 India 2020-06-12 05:09:52 102 0 1
## 192 India 2020-06-12 05:09:52 128 0 22
## 193 India 2020-06-12 05:09:52 3386 9 2354
## 194 India 2020-06-12 05:09:52 157 2 67
## 195 India 2020-06-12 05:09:52 2887 59 2259
## 196 India 2020-06-12 05:09:52 11838 265 8775
## 197 India 2020-06-12 05:09:52 14 0 2
## 198 India 2020-06-12 05:09:52 38716 349 20705
## 199 India 2020-06-12 05:09:52 4320 165 1993
## 200 India 2020-06-12 05:09:52 913 1 278
## 201 India 2020-06-12 05:09:52 8315 0 0
## 202 India 2020-06-12 05:09:52 12088 345 7292
## 203 India 2020-06-12 05:09:52 1643 15 842
## 204 India 2020-06-12 05:09:52 9768 442 3988
## 205 India 2020-06-13 03:33:14 38 0 33
## 206 India 2020-06-13 03:33:14 5429 80 3048
## 207 India 2020-06-13 03:33:14 61 0 4
## 208 India 2020-06-13 03:33:14 3319 6 1432
## 209 India 2020-06-13 03:33:14 5983 36 3266
## 210 India 2020-06-13 03:33:14 332 5 286
## 211 India 2020-06-13 03:33:14 1398 6 447
## 212 India 2020-06-13 03:33:14 30 0 2
## 213 India 2020-06-13 03:33:14 34687 1085 12731
## 214 India 2020-06-13 03:33:14 417 0 67
## 215 India 2020-06-13 03:33:14 22032 1385 15101
## 216 India 2020-06-13 03:33:14 5968 64 2260
## 217 India 2020-06-13 03:33:14 470 6 280
## 218 India 2020-06-13 03:33:14 4574 52 1820
## 219 India 2020-06-13 03:33:14 1599 8 630
## 220 India 2020-06-13 03:33:14 6245 72 2977
## 221 India 2020-06-13 03:33:14 2244 18 968
## 222 India 2020-06-13 03:33:14 135 1 54
## 223 India 2020-06-13 03:33:14 10241 431 7042
## 224 India 2020-06-13 03:33:14 97648 3590 46078
## 225 India 2020-06-13 03:33:14 366 0 73
## 226 India 2020-06-13 03:33:14 44 1 18
## 227 India 2020-06-13 03:33:14 102 0 1
## 228 India 2020-06-13 03:33:14 128 0 22
## 229 India 2020-06-13 03:33:14 3386 9 2354
## 230 India 2020-06-13 03:33:14 157 2 67
## 231 India 2020-06-13 03:33:14 2887 59 2259
## 232 India 2020-06-13 03:33:14 11838 265 8775
## 233 India 2020-06-13 03:33:14 14 0 2
## 234 India 2020-06-13 03:33:14 38716 349 20705
## 235 India 2020-06-13 03:33:14 4320 165 1993
## 236 India 2020-06-13 03:33:14 913 1 278
## 237 India 2020-06-13 03:33:14 8315 0 0
## 238 India 2020-06-13 03:33:14 12088 345 7292
## 239 India 2020-06-13 03:33:14 1643 15 842
## 240 India 2020-06-13 03:33:14 9768 442 3988
## 241 India 2020-06-14 03:33:15 38 0 33
## 242 India 2020-06-14 03:33:15 5680 80 3105
## 243 India 2020-06-14 03:33:15 67 0 4
## 244 India 2020-06-14 03:33:15 3498 8 1537
## 245 India 2020-06-14 03:33:15 6103 36 3587
## 246 India 2020-06-14 03:33:15 334 5 286
## 247 India 2020-06-14 03:33:15 1429 6 550
## 248 India 2020-06-14 03:33:15 30 0 2
## 249 India 2020-06-14 03:33:15 36824 1214 13398
## 250 India 2020-06-14 03:33:15 463 0 69
## 251 India 2020-06-14 03:33:15 22527 1415 15493
## 252 India 2020-06-14 03:33:15 6334 70 2475
## 253 India 2020-06-14 03:33:15 486 6 297
## 254 India 2020-06-14 03:33:15 4730 53 2086
## 255 India 2020-06-14 03:33:15 1617 8 672
## 256 India 2020-06-14 03:33:15 6516 79 3440
## 257 India 2020-06-14 03:33:15 2322 19 1000
## 258 India 2020-06-14 03:33:15 239 1 62
## 259 India 2020-06-14 03:33:15 10443 440 7201
## 260 India 2020-06-14 03:33:15 101141 3717 47796
## 261 India 2020-06-14 03:33:15 385 0 77
## 262 India 2020-06-14 03:33:15 44 1 22
## 263 India 2020-06-14 03:33:15 104 0 1
## 264 India 2020-06-14 03:33:15 156 0 49
## 265 India 2020-06-14 03:33:15 3498 10 2474
## 266 India 2020-06-14 03:33:15 157 2 67
## 267 India 2020-06-14 03:33:15 2986 63 2282
## 268 India 2020-06-14 03:33:15 12068 272 8898
## 269 India 2020-06-14 03:33:15 63 0 2
## 270 India 2020-06-14 03:33:15 40698 367 22047
## 271 India 2020-06-14 03:33:15 4484 174 2278
## 272 India 2020-06-14 03:33:15 961 1 278
## 273 India 2020-06-14 03:33:15 7984 0 0
## 274 India 2020-06-14 03:33:15 12616 365 7609
## 275 India 2020-06-14 03:33:15 1724 21 947
## 276 India 2020-06-14 03:33:15 10244 451 4206
## 277 India 2020-06-15 03:33:14 38 0 33
## 278 India 2020-06-15 03:33:14 5965 82 3195
## 279 India 2020-06-15 03:33:14 87 0 4
## 280 India 2020-06-15 03:33:14 3718 8 1584
## 281 India 2020-06-15 03:33:14 6290 39 3956
## 282 India 2020-06-15 03:33:14 345 5 286
## 283 India 2020-06-15 03:33:14 1512 6 631
## 284 India 2020-06-15 03:33:14 35 0 2
## 285 India 2020-06-15 03:33:14 38958 1271 14945
## 286 India 2020-06-15 03:33:14 523 0 70
## 287 India 2020-06-15 03:33:14 23038 1448 15883
## 288 India 2020-06-15 03:33:14 6749 78 2803
## 289 India 2020-06-15 03:33:14 502 6 313
## 290 India 2020-06-15 03:33:14 4878 55 2269
## 291 India 2020-06-15 03:33:14 1711 8 816
## 292 India 2020-06-15 03:33:14 6824 81 3648
## 293 India 2020-06-15 03:33:14 2407 19 1046
## 294 India 2020-06-15 03:33:14 437 1 68
## 295 India 2020-06-15 03:33:14 10641 447 7377
## 296 India 2020-06-15 03:33:14 104568 3830 49346
## 297 India 2020-06-15 03:33:14 449 0 91
## 298 India 2020-06-15 03:33:14 44 1 22
## 299 India 2020-06-15 03:33:14 107 0 1
## 300 India 2020-06-15 03:33:14 163 0 76
## 301 India 2020-06-15 03:33:14 3723 10 2594
## 302 India 2020-06-15 03:33:14 176 2 82
## 303 India 2020-06-15 03:33:14 3063 65 2327
## 304 India 2020-06-15 03:33:14 12401 282 9337
## 305 India 2020-06-15 03:33:14 63 0 4
## 306 India 2020-06-15 03:33:14 42687 397 23409
## 307 India 2020-06-15 03:33:14 4737 182 2352
## 308 India 2020-06-15 03:33:14 1046 1 315
## 309 India 2020-06-15 03:33:14 7436 0 0
## 310 India 2020-06-15 03:33:14 13118 385 7875
## 311 India 2020-06-15 03:33:14 1785 23 1077
## 312 India 2020-06-15 03:33:14 10698 463 4542
## 313 India 2020-06-16 04:33:09 41 0 33
## 314 India 2020-06-16 04:33:09 6456 88 3316
## 315 India 2020-06-16 04:33:09 91 0 7
## 316 India 2020-06-16 04:33:09 4158 8 2166
## 317 India 2020-06-16 04:33:09 6650 40 4409
## 318 India 2020-06-16 04:33:09 354 6 296
## 319 India 2020-06-16 04:33:09 1756 8 890
## 320 India 2020-06-16 04:33:09 36 0 5
## 321 India 2020-06-16 04:33:09 42829 1400 16427
## 322 India 2020-06-16 04:33:09 592 0 85
## 323 India 2020-06-16 04:33:09 24055 1505 16664
## 324 India 2020-06-16 04:33:09 7722 100 3565
## 325 India 2020-06-16 04:33:09 556 8 353
## 326 India 2020-06-16 04:33:09 5220 62 2604
## 327 India 2020-06-16 04:33:09 1763 8 905
## 328 India 2020-06-16 04:33:09 7213 89 4135
## 329 India 2020-06-16 04:33:09 2543 20 1175
## 330 India 2020-06-16 04:33:09 555 1 82
## 331 India 2020-06-16 04:33:09 10935 465 7903
## 332 India 2020-06-16 04:33:09 110744 4128 56049
## 333 India 2020-06-16 04:33:09 490 0 151
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## 747 India 2020-06-28 04:34:04 177 1 54
## 748 India 2020-06-28 04:34:04 6816 9 4500
## 749 India 2020-06-28 04:34:04 8931 59 6843
## 750 India 2020-06-28 04:34:04 428 6 335
## 751 India 2020-06-28 04:34:04 2545 13 1914
## 752 India 2020-06-28 04:34:04 177 0 55
## 753 India 2020-06-28 04:34:04 80188 2558 49301
## 754 India 2020-06-28 04:34:04 1128 2 420
## 755 India 2020-06-28 04:34:04 30709 1789 22409
## 756 India 2020-06-28 04:34:04 13427 218 8472
## 757 India 2020-06-28 04:34:04 894 9 509
## 758 India 2020-06-28 04:34:04 6966 93 4225
## 759 India 2020-06-28 04:34:04 2339 12 1724
## 760 India 2020-06-28 04:34:04 11923 191 7287
## 761 India 2020-06-28 04:34:04 4071 22 2110
## 762 India 2020-06-28 04:34:04 960 1 554
## 763 India 2020-06-28 04:34:04 12965 550 9971
## 764 India 2020-06-28 04:34:04 159133 7273 84245
## 765 India 2020-06-28 04:34:04 1092 0 432
## 766 India 2020-06-28 04:34:04 47 1 42
## 767 India 2020-06-28 04:34:04 148 0 55
## 768 India 2020-06-28 04:34:04 387 0 164
## 769 India 2020-06-28 04:34:04 6350 18 4606
## 770 India 2020-06-28 04:34:04 619 10 221
## 771 India 2020-06-28 04:34:04 5056 128 3320
## 772 India 2020-06-28 04:34:04 16944 391 13367
## 773 India 2020-06-28 04:34:04 87 0 46
## 774 India 2020-06-28 04:34:04 78335 1025 44094
## 775 India 2020-06-28 04:34:04 13436 243 4928
## 776 India 2020-06-28 04:34:04 1334 1 1071
## 777 India 2020-06-28 04:34:04 7839 0 0
## 778 India 2020-06-28 04:34:04 21549 649 14215
## 779 India 2020-06-28 04:34:04 2791 37 1912
## 780 India 2020-06-28 04:34:04 16711 629 10789
## 781 India 2020-06-29 04:33:44 76 0 45
## 782 India 2020-06-29 04:33:44 13241 169 5908
## 783 India 2020-06-29 04:33:44 182 1 60
## 784 India 2020-06-29 04:33:44 7206 10 5088
## 785 India 2020-06-29 04:33:44 9212 60 7118
## 786 India 2020-06-29 04:33:44 429 6 336
## 787 India 2020-06-29 04:33:44 2662 13 2091
## 788 India 2020-06-29 04:33:44 178 0 60
## 789 India 2020-06-29 04:33:44 83077 2623 52607
## 790 India 2020-06-29 04:33:44 1198 3 478
## 791 India 2020-06-29 04:33:44 31320 1808 22800
## 792 India 2020-06-29 04:33:44 13829 223 8917
## 793 India 2020-06-29 04:33:44 916 9 529
## 794 India 2020-06-29 04:33:44 7093 94 4316
## 795 India 2020-06-29 04:33:44 2364 12 1793
## 796 India 2020-06-29 04:33:44 13190 207 7507
## 797 India 2020-06-29 04:33:44 4189 22 2152
## 798 India 2020-06-29 04:33:44 963 1 586
## 799 India 2020-06-29 04:33:44 13186 557 10084
## 800 India 2020-06-29 04:33:44 164626 7429 86575
## 801 India 2020-06-29 04:33:44 1185 0 455
## 802 India 2020-06-29 04:33:44 47 1 42
## 803 India 2020-06-29 04:33:44 148 0 55
## 804 India 2020-06-29 04:33:44 415 0 164
## 805 India 2020-06-29 04:33:44 6614 21 4743
## 806 India 2020-06-29 04:33:44 619 10 221
## 807 India 2020-06-29 04:33:44 5216 133 3526
## 808 India 2020-06-29 04:33:44 17271 399 13611
## 809 India 2020-06-29 04:33:44 88 0 49
## 810 India 2020-06-29 04:33:44 82275 1079 45537
## 811 India 2020-06-29 04:33:44 14419 247 5172
## 812 India 2020-06-29 04:33:44 1346 1 1079
## 813 India 2020-06-29 04:33:44 7285 0 0
## 814 India 2020-06-29 04:33:44 22147 660 14808
## 815 India 2020-06-29 04:33:44 2823 38 2018
## 816 India 2020-06-29 04:33:44 17283 639 11193
## 817 India 2020-06-30 04:33:48 90 0 46
## 818 India 2020-06-30 04:33:48 13891 180 6232
## 819 India 2020-06-30 04:33:48 187 1 61
## 820 India 2020-06-30 04:33:48 7752 11 5333
## 821 India 2020-06-30 04:33:48 9640 62 7390
## 822 India 2020-06-30 04:33:48 435 6 349
## 823 India 2020-06-30 04:33:48 2761 13 2173
## 824 India 2020-06-30 04:33:48 203 0 77
## 825 India 2020-06-30 04:33:48 85161 2680 56235
## 826 India 2020-06-30 04:33:48 1198 3 478
## 827 India 2020-06-30 04:33:48 31938 1827 23240
## 828 India 2020-06-30 04:33:48 14210 232 9502
## 829 India 2020-06-30 04:33:48 942 9 556
## 830 India 2020-06-30 04:33:48 7237 95 4585
## 831 India 2020-06-30 04:33:48 2426 15 1845
## 832 India 2020-06-30 04:33:48 14295 226 7683
## 833 India 2020-06-30 04:33:48 4189 22 2152
## 834 India 2020-06-30 04:33:48 964 1 616
## 835 India 2020-06-30 04:33:48 13370 564 10199
## 836 India 2020-06-30 04:33:48 169883 7610 88960
## 837 India 2020-06-30 04:33:48 1227 0 494
## 838 India 2020-06-30 04:33:48 47 1 42
## 839 India 2020-06-30 04:33:48 148 0 55
## 840 India 2020-06-30 04:33:48 434 0 168
## 841 India 2020-06-30 04:33:48 6859 23 4946
## 842 India 2020-06-30 04:33:48 619 10 221
## 843 India 2020-06-30 04:33:48 5418 138 3764
## 844 India 2020-06-30 04:33:48 17660 405 13618
## 845 India 2020-06-30 04:33:48 88 0 50
## 846 India 2020-06-30 04:33:48 86224 1141 47749
## 847 India 2020-06-30 04:33:48 15394 253 5582
## 848 India 2020-06-30 04:33:48 1380 1 1085
## 849 India 2020-06-30 04:33:48 7004 0 0
## 850 India 2020-06-30 04:33:48 22828 672 15506
## 851 India 2020-06-30 04:33:48 2831 39 2111
## 852 India 2020-06-30 04:33:48 17907 653 11719
## 853 India 2020-07-01 04:33:52 97 0 50
## 854 India 2020-07-01 04:33:52 14595 187 6511
## 855 India 2020-07-01 04:33:52 191 1 62
## 856 India 2020-07-01 04:33:52 8227 12 5647
## 857 India 2020-07-01 04:33:52 10043 67 7687
## 858 India 2020-07-01 04:33:52 440 6 364
## 859 India 2020-07-01 04:33:52 2860 13 2250
## 860 India 2020-07-01 04:33:52 213 0 82
## 861 India 2020-07-01 04:33:52 87360 2742 58348
## 862 India 2020-07-01 04:33:52 1315 3 596
## 863 India 2020-07-01 04:33:52 32557 1846 23662
## 864 India 2020-07-01 04:33:52 14548 236 9972
## 865 India 2020-07-01 04:33:52 953 10 580
## 866 India 2020-07-01 04:33:52 7497 101 4722
## 867 India 2020-07-01 04:33:52 2490 15 1884
## 868 India 2020-07-01 04:33:52 15242 246 7918
## 869 India 2020-07-01 04:33:52 4442 24 2306
## 870 India 2020-07-01 04:33:52 973 1 648
## 871 India 2020-07-01 04:33:52 13593 572 10395
## 872 India 2020-07-01 04:33:52 174761 7855 90911
## 873 India 2020-07-01 04:33:52 1234 0 553
## 874 India 2020-07-01 04:33:52 52 1 42
## 875 India 2020-07-01 04:33:52 160 0 122
## 876 India 2020-07-01 04:33:52 459 0 168
## 877 India 2020-07-01 04:33:52 7065 25 5189
## 878 India 2020-07-01 04:33:52 714 12 272
## 879 India 2020-07-01 04:33:52 5568 144 3867
## 880 India 2020-07-01 04:33:52 18014 413 14220
## 881 India 2020-07-01 04:33:52 89 0 52
## 882 India 2020-07-01 04:33:52 90167 1201 50074
## 883 India 2020-07-01 04:33:52 16339 260 7294
## 884 India 2020-07-01 04:33:52 1388 1 1086
## 885 India 2020-07-01 04:33:52 6915 0 0
## 886 India 2020-07-01 04:33:52 23492 697 16084
## 887 India 2020-07-01 04:33:52 2881 41 2231
## 888 India 2020-07-01 04:33:52 18559 668 12130
## 889 India 2020-07-02 04:33:46 100 0 50
## 890 India 2020-07-02 04:33:46 15252 193 6988
## 891 India 2020-07-02 04:33:46 195 1 66
## 892 India 2020-07-02 04:33:46 8582 12 5851
## 893 India 2020-07-02 04:33:46 10249 70 7946
## 894 India 2020-07-02 04:33:46 446 6 367
## 895 India 2020-07-02 04:33:46 2940 14 2303
## 896 India 2020-07-02 04:33:46 215 0 86
## 897 India 2020-07-02 04:33:46 89802 2803 59992
## 898 India 2020-07-02 04:33:46 1387 4 670
## 899 India 2020-07-02 04:33:46 33232 1867 24030
## 900 India 2020-07-02 04:33:46 14941 240 10499
## 901 India 2020-07-02 04:33:46 979 10 614
## 902 India 2020-07-02 04:33:46 7695 105 4856
## 903 India 2020-07-02 04:33:46 2521 15 1931
## 904 India 2020-07-02 04:33:46 16514 253 8063
## 905 India 2020-07-02 04:33:46 4593 24 2439
## 906 India 2020-07-02 04:33:46 990 1 694
## 907 India 2020-07-02 04:33:46 13861 581 10655
## 908 India 2020-07-02 04:33:46 180298 8053 93154
## 909 India 2020-07-02 04:33:46 1260 0 579
## 910 India 2020-07-02 04:33:46 52 1 42
## 911 India 2020-07-02 04:33:46 160 0 123
## 912 India 2020-07-02 04:33:46 459 0 168
## 913 India 2020-07-02 04:33:46 7316 25 5353
## 914 India 2020-07-02 04:33:46 714 12 272
## 915 India 2020-07-02 04:33:46 5668 149 3867
## 916 India 2020-07-02 04:33:46 18312 421 14574
## 917 India 2020-07-02 04:33:46 101 0 53
## 918 India 2020-07-02 04:33:46 94049 1264 52926
## 919 India 2020-07-02 04:33:46 17357 267 8082
## 920 India 2020-07-02 04:33:46 1396 1 1093
## 921 India 2020-07-02 04:33:46 6832 0 0
## 922 India 2020-07-02 04:33:46 24056 718 16629
## 923 India 2020-07-02 04:33:46 2947 41 2317
## 924 India 2020-07-02 04:33:46 19170 683 12528
## 925 India 2020-07-03 04:33:54 109 0 51
## 926 India 2020-07-03 04:33:54 16097 198 7313
## 927 India 2020-07-03 04:33:54 195 1 66
## 928 India 2020-07-03 04:33:54 9013 12 6106
## 929 India 2020-07-03 04:33:54 10471 77 8020
## 930 India 2020-07-03 04:33:54 450 6 389
## 931 India 2020-07-03 04:33:54 3013 14 2385
## 932 India 2020-07-03 04:33:54 230 0 89
## 933 India 2020-07-03 04:33:54 92175 2864 63007
## 934 India 2020-07-03 04:33:54 1482 4 734
## 935 India 2020-07-03 04:33:54 33913 1886 24593
## 936 India 2020-07-03 04:33:54 15509 251 11019
## 937 India 2020-07-03 04:33:54 1014 10 628
## 938 India 2020-07-03 04:33:54 7849 115 4974
## 939 India 2020-07-03 04:33:54 2584 15 1983
## 940 India 2020-07-03 04:33:54 18016 272 8334
## 941 India 2020-07-03 04:33:54 4753 25 2640
## 942 India 2020-07-03 04:33:54 990 1 730
## 943 India 2020-07-03 04:33:54 14106 589 10815
## 944 India 2020-07-03 04:33:54 186626 8178 101172
## 945 India 2020-07-03 04:33:54 1279 0 617
## 946 India 2020-07-03 04:33:54 56 1 42
## 947 India 2020-07-03 04:33:54 162 0 126
## 948 India 2020-07-03 04:33:54 501 0 182
## 949 India 2020-07-03 04:33:54 7545 27 5502
## 950 India 2020-07-03 04:33:54 802 12 331
## 951 India 2020-07-03 04:33:54 5784 152 4144
## 952 India 2020-07-03 04:33:54 18662 430 14948
## 953 India 2020-07-03 04:33:54 102 0 53
## 954 India 2020-07-03 04:33:54 98392 1321 56021
## 955 India 2020-07-03 04:33:54 18570 275 9069
## 956 India 2020-07-03 04:33:54 1435 1 1146
## 957 India 2020-07-03 04:33:54 6031 0 0
## 958 India 2020-07-03 04:33:54 24825 735 17221
## 959 India 2020-07-03 04:33:54 2984 42 2405
## 960 India 2020-07-03 04:33:54 19819 699 13037
## 961 India 2020-07-04 04:33:51 116 0 54
## 962 India 2020-07-04 04:33:51 16934 206 7632
## 963 India 2020-07-04 04:33:51 252 1 75
## 964 India 2020-07-04 04:33:51 9673 14 6349
## 965 India 2020-07-04 04:33:51 10954 80 8214
## 966 India 2020-07-04 04:33:51 457 6 393
## 967 India 2020-07-04 04:33:51 3065 14 2437
## 968 India 2020-07-04 04:33:51 257 0 96
## 969 India 2020-07-04 04:33:51 94695 2923 65624
## 970 India 2020-07-04 04:33:51 1482 4 734
## 971 India 2020-07-04 04:33:51 34600 1904 24933
## 972 India 2020-07-04 04:33:51 16003 255 11691
## 973 India 2020-07-04 04:33:51 1033 10 667
## 974 India 2020-07-04 04:33:51 8019 119 5075
## 975 India 2020-07-04 04:33:51 2695 15 2001
## 976 India 2020-07-04 04:33:51 19710 293 8805
## 977 India 2020-07-04 04:33:51 4964 25 2841
## 978 India 2020-07-04 04:33:51 1001 1 777
## 979 India 2020-07-04 04:33:51 14297 593 11049
## 980 India 2020-07-04 04:33:51 192990 8376 104687
## 981 India 2020-07-04 04:33:51 1316 0 639
## 982 India 2020-07-04 04:33:51 62 1 43
## 983 India 2020-07-04 04:33:51 162 0 126
## 984 India 2020-07-04 04:33:51 539 0 228
## 985 India 2020-07-04 04:33:51 8106 29 5705
## 986 India 2020-07-04 04:33:51 802 12 331
## 987 India 2020-07-04 04:33:51 5937 157 4266
## 988 India 2020-07-04 04:33:51 19052 440 15281
## 989 India 2020-07-04 04:33:51 102 0 53
## 990 India 2020-07-04 04:33:51 102721 1385 58378
## 991 India 2020-07-04 04:33:51 20462 283 10195
## 992 India 2020-07-04 04:33:51 1525 1 1199
## 993 India 2020-07-04 04:33:51 4999 0 0
## 994 India 2020-07-04 04:33:51 25797 749 17597
## 995 India 2020-07-04 04:33:51 3048 42 2481
## 996 India 2020-07-04 04:33:51 20488 717 13571
## 997 India 2020-07-05 04:33:46 119 0 66
## 998 India 2020-07-05 04:33:46 17699 218 8008
## 999 India 2020-07-05 04:33:46 259 1 76
## 1000 India 2020-07-05 04:33:46 10668 14 6657
## 1001 India 2020-07-05 04:33:46 11700 89 8686
## 1002 India 2020-07-05 04:33:46 460 6 395
## 1003 India 2020-07-05 04:33:46 3161 14 2549
## 1004 India 2020-07-05 04:33:46 271 0 96
## 1005 India 2020-07-05 04:33:46 97200 3004 68256
## 1006 India 2020-07-05 04:33:46 1684 6 825
## 1007 India 2020-07-05 04:33:46 35312 1925 25406
## 1008 India 2020-07-05 04:33:46 16548 260 12257
## 1009 India 2020-07-05 04:33:46 1046 11 704
## 1010 India 2020-07-05 04:33:46 8246 127 5143
## 1011 India 2020-07-05 04:33:46 2739 17 2035
## 1012 India 2020-07-05 04:33:46 21549 335 9244
## 1013 India 2020-07-05 04:33:46 5204 25 3048
## 1014 India 2020-07-05 04:33:46 1005 1 826
## 1015 India 2020-07-05 04:33:46 14604 598 11234
## 1016 India 2020-07-05 04:33:46 200064 8671 108082
## 1017 India 2020-07-05 04:33:46 1325 0 667
## 1018 India 2020-07-05 04:33:46 62 1 43
## 1019 India 2020-07-05 04:33:46 164 0 130
## 1020 India 2020-07-05 04:33:46 563 0 228
## 1021 India 2020-07-05 04:33:46 8601 34 5934
## 1022 India 2020-07-05 04:33:46 802 12 331
## 1023 India 2020-07-05 04:33:46 6109 162 4306
## 1024 India 2020-07-05 04:33:46 19532 447 15640
## 1025 India 2020-07-05 04:33:46 103 0 58
## 1026 India 2020-07-05 04:33:46 107001 1450 60592
## 1027 India 2020-07-05 04:33:46 22312 288 11537
## 1028 India 2020-07-05 04:33:46 1546 1 1202
## 1029 India 2020-07-05 04:33:46 4629 0 0
## 1030 India 2020-07-05 04:33:46 26554 773 18154
## 1031 India 2020-07-05 04:33:46 3093 42 2502
## 1032 India 2020-07-05 04:33:46 21231 736 14166
## 1033 India 2020-07-06 04:33:57 125 0 72
## 1034 India 2020-07-06 04:33:57 18697 232 8422
## 1035 India 2020-07-06 04:33:57 269 1 78
## 1036 India 2020-07-06 04:33:57 11388 14 7125
## 1037 India 2020-07-06 04:33:57 11876 95 8765
## 1038 India 2020-07-06 04:33:57 466 6 395
## 1039 India 2020-07-06 04:33:57 3207 14 2601
## 1040 India 2020-07-06 04:33:57 271 0 106
## 1041 India 2020-07-06 04:33:57 99444 3067 71339
## 1042 India 2020-07-06 04:33:57 1761 7 936
## 1043 India 2020-07-06 04:33:57 36037 1943 25892
## 1044 India 2020-07-06 04:33:57 17005 265 12944
## 1045 India 2020-07-06 04:33:57 1063 11 737
## 1046 India 2020-07-06 04:33:57 8429 132 5255
## 1047 India 2020-07-06 04:33:57 2781 19 2045
## 1048 India 2020-07-06 04:33:57 23474 372 9847
## 1049 India 2020-07-06 04:33:57 5429 25 3174
## 1050 India 2020-07-06 04:33:57 1005 1 826
## 1051 India 2020-07-06 04:33:57 14930 608 11411
## 1052 India 2020-07-06 04:33:57 206619 8822 111740
## 1053 India 2020-07-06 04:33:57 1366 0 688
## 1054 India 2020-07-06 04:33:57 62 1 43
## 1055 India 2020-07-06 04:33:57 186 0 130
## 1056 India 2020-07-06 04:33:57 590 0 231
## 1057 India 2020-07-06 04:33:57 9070 36 6224
## 1058 India 2020-07-06 04:33:57 802 12 331
## 1059 India 2020-07-06 04:33:57 6283 164 4408
## 1060 India 2020-07-06 04:33:57 20164 456 15928
## 1061 India 2020-07-06 04:33:57 123 0 61
## 1062 India 2020-07-06 04:33:57 111151 1510 62778
## 1063 India 2020-07-06 04:33:57 23902 295 12703
## 1064 India 2020-07-06 04:33:57 1568 1 1202
## 1065 India 2020-07-06 04:33:57 4913 0 0
## 1066 India 2020-07-06 04:33:57 27707 785 18761
## 1067 India 2020-07-06 04:33:57 3124 42 2524
## 1068 India 2020-07-06 04:33:57 22126 757 14711
df1_IND <- data.frame(state=c("Confirmed","Recovered","Deaths"),
cases=c(sum(df_IND$Confirmed),sum(df_IND$Recovered),sum(df_IND$Deaths)))
ggplot(data=df1_IND, aes(x=state, y=cases)) +
geom_bar(stat="identity", fill="steelblue")+
geom_text(aes(label=cases), vjust=-0.3, size=3.5)+
theme_minimal()
ggplot(data=df1_IND, aes(x=state, y=cases, fill=state)) +
geom_bar(stat="identity")+
geom_text(aes(label=cases), vjust=1.5, size=3.5)+
theme_minimal()
# convert dates
df_IND$Date <- as.Date(df_IND$ObservationDate, format = '%m/%d/%y')
df_IND$ObservationDate <- NULL
df_IND$Last.Update <- NULL
df_IND <- dplyr::group_by(df_IND, Date) %>% dplyr::summarize(n=n(),
Confirmed=sum(Confirmed),
Deaths=sum(Deaths),
Recovered=sum(Recovered))
n <- nrow(df_IND)
print(paste0('Observations: ', n))
## [1] "Observations: 158"
# add a few more features
df_IND$Active <- df_IND$Confirmed - df_IND$Recovered - df_IND$Deaths
df_IND$MortRate <- df_IND$Deaths / df_IND$Confirmed
df_IND$RecRate <- df_IND$Recovered / df_IND$Confirmed
df_IND$Rec_vs_Mort <- df_IND$Recovered / df_IND$Deaths
df_IND$DiffConf <- 0
df_IND$DiffConf[2:nrow(df_IND)] <- diff(df_IND$Confirmed)
df_IND$RelIncrease <- c(NaN, df_IND$DiffConf[2:n] / df_IND$Confirmed[1:n-1])
df_IND$DoublingDays <- round(log(2)/log(1+df_IND$RelIncrease),2)
df_IND$DiffDeath <- 0
df_IND$DiffDeath[2:nrow(df_IND)] <- diff(df_IND$Deaths)
df_IND$RelIncD <- c(NaN, df_IND$DiffDeath[2:n] / df_IND$Deaths[1:n-1])
df_IND$DoublingDaysD <- round(log(2)/log(1+df_IND$RelIncD),2)
# show data frame
head(df_IND)
## # A tibble: 6 x 15
## Date n Confirmed Deaths Recovered Active MortRate RecRate
## <date> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2020-01-30 1 1 0 0 1 0 0
## 2 2020-01-31 1 1 0 0 1 0 0
## 3 2020-02-01 1 1 0 0 1 0 0
## 4 2020-02-02 1 2 0 0 2 0 0
## 5 2020-02-03 1 3 0 0 3 0 0
## 6 2020-02-04 1 3 0 0 3 0 0
## # ... with 7 more variables: Rec_vs_Mort <dbl>, DiffConf <dbl>,
## # RelIncrease <dbl>, DoublingDays <dbl>, DiffDeath <dbl>, RelIncD <dbl>,
## # DoublingDaysD <dbl>
#-------------------------------------------------------------------------------
# Plotting Graphs for India Analysis.
#-------------------------------------------------------------------------------
plot(df_IND$Date, df_IND$Confirmed, main='Confirmed Cases', type='b')
grid()
plot(df_IND$Date, log10(df_IND$Confirmed), main='Confirmed Cases - Log Scale', type='b')
grid()
plot(df_IND$Date, df_IND$DiffConf, main='Absolute Increase of Confirmed Cases', type='b')
grid()
plot(df_IND$Date, df_IND$RelIncrease, main='Relative Change vs Previous Day', type='b', ylim=c(0,0.1))
grid()
plot(df_IND$Date, df_IND$DoublingDays, main='Confirmed - Theoretical days until next doubling', type='b',ylim=c(0,1000))
grid()
plot(df_IND$Date, df_IND$Deaths, main='Deaths', type='b')
grid()
plot(df_IND$Date, log10(df_IND$Deaths), main='Deaths - Log Scale', type='b')
grid()
plot(df_IND$Date, df_IND$DiffDeath, main='Absolute Increase of Deaths', type='b')
grid()
plot(df_IND$Date, df_IND$RelIncD, main='Deaths - Relative Change vs Previous Day', type='b', ylim=c(0,0.05))
grid()
plot(df_IND$Date, df_IND$Recovered, main='Recovered', type='b')
grid()
plot(df_IND$Date, df_IND$Active, main='Active', type='b')
grid()
plot(df_IND$Date, df_IND$RecRate, pch=16, col='darkgreen', type='b', ylab='Recovery Ratio', main='Recovery Ratio')
grid()
plot(df_IND$Date, df_IND$MortRate, pch=16, col='red', type='b', ylab='Death Ratio', main='Death Ratio')
grid()
plot(df_IND$Date, df_IND$Rec_vs_Mort, pch=16, col='blue', type='b', ylab='Recovered : Deaths', main='Recovered : Deaths')
grid()
# bubble plot (death ratio, recovery ratio, total positive cases)
ggplot(df_IND, aes(x=RecRate, y=MortRate, size=Confirmed, color=Date)) +
geom_point(alpha=0.7) + ggtitle('Ratios') + theme(legend.position="bottom")
# store in CSV for further processing
write.csv(df_IND, file='IND.csv')