Using data blending, create a report on Confirmed Cases in China and Top Six Countries$-$ including US$,$ Italy, Iran, Spain, Germany and France$-$ as both China Covid$19$ data and Other countries covid$19$ data are captured on different files. Show how confirmed cases change in time for China Vs$.$ Top Six Countries. Use Covid$19\_$China.xlsx and Covid$19\_$Others.xlsx$.$

Covid$19$ China.xlsx

Covid$19$ Others.xlsx

Please upload Tableau Package Workbook $(.$twbx$,$ not $.$twb$)$

On Tableau File$->$Save As$->$In the drop down menu Save as type Tableau Packaged Workbook.

File type is restricted to $.$twbx extension upon uploading, no other types are allowed.

DateA$1/22/2020|$ Hong Kong$1/22/2020$ Macau$1/22/20201/22/2020$ Taiwan$1/22/2020$ Washington$1/22/20201/22/20201/23/2020$ Hong Kong$1/23/2020$ Macau$1/23/20201/23/2020|$Taiwan$1/23/2020$ Washington$1/23/20201/23/20201/23/20201/23/20201/23/20201/23/20201/23/20201/23/20201/23/20201/23/20201/24/2020$ Taiwan$1/24/2020|$ Hong Kong$1/24/2020|$ Macau$1/24/2020$ Washington$1/24/2020|$ Chicago$1/24/2020$Province$/$State$1/24/20201/24/20201/24/20201/24/20201/24/2020$B$1/25/2020]$ Hong Kong$1/25/2020$Taiwan$1/25/2020$ Macau$1/25/2020|$ Washington$1/25/2020||$linois$1/25/20201/25/20201/25/202$ocovid$\_$othersCountry$/$RegionHong Kong$|$MacauTaiwanUSJapanThailandSouth KoreaHong KongMacauTaiwanUSJapanThailandSouth KoreaSingaporePhilippinesMalaysia$|$Vietnam$|$AustraliaMexicoBrazilColombiaTaiwan$|$Hong KongMacauUSUSJapanCThailandSouth KoreaSingaporeVietnamFranceHong KongTaiwanMacau$|$USUS$|$JapanThailandSouth KoreaDConfirmed$112212211112003221125232252272$EDeaths$00000$FRecovered$0000000000000$

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L$2091011121$ Observation Date$13141516171819202122232425262728293031323334393637$File$3839404142$HomeReadyInsert Paqe Layout FormulasAi PROTECTED VIEW Be careful files from the Internet can contain viruses. Unless you need to edit, it's safer to stay in Protected View.Province$/$State$1/22/2020$ Anhui$1/22/2020$ Beijing$1/22/2020$ Chongqing$1/22/2020$ Fujian$1/22/2020$ Gansu$1/22/2020$ Guangdong$1/22/2020$ Guangxi$1/22/2020$ Guizhou$1/22/2020$ Hainan$1/22/2020$ Hebei$1/22/2020$ Heilongjiang$1/22/2020$ Henan$1/22/2020$ Hubei$1/22/2020$ Hunan$1/22/2020$ Inner Mongolia$1/22/2020$ Jiangsu$1/22/2020$ Jiangxi$1/22/2020$ Jilin$1/22/2020$ Liaoning$1/22/2020$ Ningxia$1/22/2020$ Qinghai$1/22/2020$ Shaanxi$1/22/2020$ Shandong$1/22/2020$ Shanghai$1/22/2020$ Shanxi$1/22/2020$ Sichuan$1/22/2020$ Tianjin$1/22/2020$ Tibet$1/22/2020$ Xinjiang$1/22/2020$ Yunnan$1/22/2020$ Zhejiang$1/23/2020$ Anhui$1/23/2020$ Beijing$1/23/2020$ Chongqing$1/23/2020$ Fujian$1/23/2020$ Gansu$1/23/2020$Guangdong$1/23/2020$ Guangxi$1/23/2020$ Guizhou$1/23/2020$ Hainan$1/23/2020$ HebeiDataMainland ChinaCountry$/$RegionMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaMainland ChinaReviewMainland ChinaViewDConfirmed Deaths$114616214105444$A$2219141095255$HelpE$1)170000))9$ Tell me what you want to do$)$FRecoveredC$0$C$28$C$0$CGHEnable EditingCovid$19$ China $[$Protected View$]-$ ExcelKMN