Visualize confirmed cases in 2020 for Canada, China, Spain, Italy, and USA
GET https://covid19.richdataservices.com/rds/api/query/int/jhu_country/tabulate?dims=date_stamp,iso3166_1&where=(year_stamp=2020) AND (iso3166_1=US OR iso3166_1=CA OR iso3166_1=ES OR iso3166_1=IT OR iso3166_1=CN)&measure=cnt_confirmed:SUM(cnt_confirmed)&inject=true&metadata=true&orderBy=date_stamp ASC,iso3166_1 ASC&totals=true&format=amcharts
Compare how COVID-19 cases have increased over time in different countries. See it in the tabulation engine, or click over to the Visualize tab in the Qodex app to see the graph displayed below.
Of course, you can also leave off the format parameter to have the data returned cell by cell. An example of this is available in the Example Responses section.
Request Params
| Key | Datatype | Required | Description |
|---|---|---|---|
dims | string | Our dimensions here are date_stamp and iso3166_1 (country code). This will return a record (or cell, if you're viewing in the tab engine) for each country for each day. | |
where | string | Using the AND and OR operators, we are telling RDS to only return data from the year 2020, and only from the countries of interest. |
Find all the country codes by sending the following request. Note that you will need to use the codeValue property and not thename property when querying. http://covid19.richdataservices.com/rds/api/catalog/int/jhu_country/classification/iso3166_1/codes |
| measure | string | | In this time series we want the confirmed count for each country on an specific date. We will compute the count as the sum of confirmed cases for a country on a specific date (there will only be one value per date so the sum will give us the correct number), we will create a computed variable, cnt_confirmed, as the Sum of the cnt_confirmed variable in the data product. The sum can only be used because we used the date_stamp as a dimension. |
| inject | boolean | | By setting inject to true, we tell RDS that we want the country's name (ex: "China") instead of its code (ex: "CN") |
| metadata | boolean | | Including metadata tells RDS that we want all of the variable metadata returned with our query. This is useful when populating a visualization, or just to give more context to the data. |
| orderBy | string | | We will order date by ascending order, creating a time series, and country by ascending order, sorting them alphabetically. |
| totals | boolean | | Choose whether or not to include totals for the dimensions |
| format | string | | Our desired charting library, used to create the visualization you see in the visualization tab. |
RESPONSES
status: OK
{"dataProvider":[{"date_stamp":"2020-01-22","iso3166_1":"China","cnt_confirmed":547},{"date_stamp":"2020-01-22","iso3166_1":"United States of America","cnt_confirmed":1},{"date_stamp":"2020-01-23","iso3166_1":"China","cnt_confirmed":639},{"date_stamp":"2020-01-23","iso3166_1":"United States of America","cnt_confirmed":1},{"date_stamp":"2020-01-24","iso3166_1":"China","cnt_confirmed":916},{"date_stamp":"2020-01-24","iso3166_1":"United States of America","cnt_confirmed":2},{"date_stamp":"2020-01-25","iso3166_1":"China","cnt_confirmed":1399},{"date_stamp":"2020-01-25","iso3166_1":"United States of America","cnt_confirmed":2},{"date_stamp":"2020-01-26","iso3166_1":"Canada","cnt_confirmed":1},{"date_stamp":"2020-01-26","iso3166_1":"China","cnt_confirmed":2062},{"date_stamp":"2020-01-26","iso3166_1":"United States of America","cnt_confirmed":5},{"date_stamp":"2020-01-27","iso3166_1":"Canada","cnt_confirmed":1},{"date_stamp":"2020-01-27","iso3166_1":"China","cnt_confirmed":2863},{"date_stamp":"2020-01-27","iso3166_1":"United States of America","cnt_confirmed":5},{"date_stamp":"2020-01-28","iso3166_1":"Canada","cnt_confirmed":2},{"date_stamp":"2020-01-28","iso3166_1":"China","cnt_confirmed":5494},{"date_stamp":"2020-01-28","iso3166_1":"United States of America","cnt_confirmed":5},{"date_stamp":"2020-01-29","iso3166_1":"Canada","cnt_confirmed":2},{"date_stamp":"2020-01-29","iso3166_1":"China","cnt_confirmed":6070},{"date_stamp":"2020-01-29","iso3166_1":"United States of America","cnt_confirmed":5},{"date_stamp":"2020-01-30","iso3166_1":"Canada","cnt_confirmed":3},{"date_stamp":"2020-01-30","iso3166_1":"China","cnt_confirmed":8124},{"date_stamp":"2020-01-30","iso3166_1":"United States of America","cnt_confirmed":5},{"date_stamp":"2020-01-31","iso3166_1":"Canada","cnt_confirmed":3},{"date_stamp":"2020-01-31","iso3166_1":"China","cnt_confirmed":9783},{"date_stamp":"2020-01-31","iso3166_1":"Italy","cnt_confirmed":2},{"date_stamp":"2020-01-31","iso3166_1":"United States of America","cnt_confirmed":6},{"date_stamp":"2020-02-01","iso3166_1":"Canada","cnt_confirmed":4},{"date_stamp":"2020-02-01","iso3166_1":"China","cnt_confirmed":11871},{"date_stamp":"2020-02-01","iso3166_1":"Spain","cnt_confirmed":1},{"date_stamp":"2020-02-01","iso3166_1":"Italy","cnt_confirmed":2},{"date_stamp":"2020-02-01","iso3166_1":"United States of America","cnt_confirmed":8},{"date_stamp":"2020-02-02","iso3166_1":"Canada","cnt_confirmed":4},{"date_stamp":"2020-02-02","iso3166_1":"China","cnt_confirmed":16607},{"date_stamp":"2020-02-02","iso3166_1":"Spain","cnt_confirmed":1},{"date_stamp":"2020-02-02","iso3166_1":"Italy","cnt_confirmed":2},{"date_stamp":"2020-02-02","iso3166_1":"United States of America","cnt_confirmed":8},{"date_stamp":"2020-02-03","iso3166_1":"Canada","cnt_confirmed":4},{"date_stamp":"2020-02-03","iso3166_1":"China","cnt_confirmed":19693},{"date_stamp":"2020-02-03","iso3166_1":"Spain","cnt_confirmed":1},{"date_stamp":"2020-02-03","iso3166_1":"Italy","cnt_confirmed":2},{"date_stamp":"2020-02-03","iso3166_1":"United States of America","cnt_confirmed":11},{"date_stamp":"2020-02-04","iso3166_1":"Canada","cnt_confirmed":4},{"date_stamp":"2020-02-04","iso3166_1":"China","cnt_confirmed":23680},{"date_stamp":"2020-02-04","iso3166_1":"Spain","cnt_confirmed":1},{"date_stamp":"2020-02-04","iso3166_1":"Italy","cnt_confirmed":2},{"date_stamp":"2020-02-04","iso3166_1":"United States of 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