JSON - Adding Multiple rows in SharePoint Custom List in one row

[milind]

I have local weather api which gives me JSON output. It have current weather node and another node for 7 days forecast. Below is the JSON output

Now I created flow as below

1. Created HTTP action to get API in JSON
2. Then, I created  JSON Parser by providing schema 
3. Then, I created COMPOSE and selected current node from the JSON Parser output
4. Then, I created Create Item for SharePoint and added current weather data into SharePoint
5. Then, Created Apply Each and selected forecastday from JSON Parser output (here I got stuck and I want to update SharePoint list in one line)

My SharePoint Custom list structure

1. Title (for today date store)
2. CurrentTemp (for Current Tempearture)
3. CurrentText (for Current Tempearture Text)
4. Day_1 (next day date from forecast)
5. Day_1_h (next day high tempreature from forecastday) 
6. Day_1_L (next day low tempreature from forecastday)
7. Day_2 (next day date from forecast)
8. Day_2_h (next day high tempreature from forecastday) 
9. Day_2_L (next day low tempreature from forecastday)
10. Day_3 (next day date from forecast)
11. Day_3_h (next day high tempreature from forecastday) 
12. Day_3_L (next day low tempreature from forecastday)
13. Day_4 (next day date from forecast)
14. Day_4_h (next day high tempreature from forecastday) 
15. Day_4_L (next day low tempreature from forecastday)
16. Day_5 (next day date from forecast)
17. Day_5_h (next day high tempreature from forecastday) 
18. Day_5_L (next day low tempreature from forecastday)
19. Day_6 (next day date from forecast)
20. Day_6_h (next day high tempreature from forecastday) 
21. Day_6_L (next day low tempreature from forecastday)
22. Day_7 (next day date from forecast)
23. Day_7_h (next day high tempreature from forecastday) 
24. Day_7_L (next day low tempreature from forecastday)

I am looking for any suggestion to improve my flow or solve my issue. Please help

[v-bacao-msft]

Hi @milind,

Could you provide the specific content of the JSON output? An example of data for a set of JSON output content.

Because the content below the forecast has not been expanded, I don't know how its format and basic content are.

If you could provide examples of data in the same format, we are more convenient to test here.

Please provide more details.

Best Regards,

[milind]

Below is original JSON data

{"location":{"name":"Kuwait City","region":"Al Kuwayt","country":"Kuwait","lat":29.37,"lon":47.96,"tz_id":"Asia/Kuwait","localtime_epoch":1548246586,"localtime":"2019-01-23 15:29"},"current":{"last_updated_epoch":1548245725,"last_updated":"2019-01-23 15:15","temp_c":16.0,"temp_f":60.8,"is_day":1,"condition":{"text":"Sunny","icon":"//cdn.apixu.com/weather/64x64/day/113.png","code":1000},"wind_mph":10.5,"wind_kph":16.9,"wind_degree":50,"wind_dir":"NE","pressure_mb":1017.0,"pressure_in":30.5,"precip_mm":0.0,"precip_in":0.0,"humidity":39,"cloud":0,"feelslike_c":16.0,"feelslike_f":60.8,"vis_km":10.0,"vis_miles":6.0,"uv":5.0},"forecast":{"forecastday":[{"date":"2019-01-23","date_epoch":1548201600,"day":{"maxtemp_c":18.9,"maxtemp_f":66.0,"mintemp_c":10.9,"mintemp_f":51.6,"avgtemp_c":15.6,"avgtemp_f":60.1,"maxwind_mph":7.4,"maxwind_kph":11.9,"totalprecip_mm":0.0,"totalprecip_in":0.0,"avgvis_km":17.5,"avgvis_miles":10.0,"avghumidity":34.0,"condition":{"text":"Partly cloudy","icon":"//cdn.apixu.com/weather/64x64/day/116.png","code":1003},"uv":4.9},"astro":{"sunrise":"06:42 AM","sunset":"05:19 PM","moonrise":"07:57 PM","moonset":"08:28 AM"}},{"date":"2019-01-24","date_epoch":1548288000,"day":{"maxtemp_c":19.3,"maxtemp_f":66.7,"mintemp_c":18.1,"mintemp_f":64.6,"avgtemp_c":18.4,"avgtemp_f":65.1,"maxwind_mph":9.4,"maxwind_kph":15.1,"totalprecip_mm":0.0,"totalprecip_in":0.0,"avgvis_km":20.0,"avgvis_miles":12.0,"avghumidity":47.0,"condition":{"text":"Partly cloudy","icon":"//cdn.apixu.com/weather/64x64/day/116.png","code":1003},"uv":5.3},"astro":{"sunrise":"06:41 AM","sunset":"05:19 PM","moonrise":"09:04 PM","moonset":"09:12 AM"}},{"date":"2019-01-25","date_epoch":1548374400,"day":{"maxtemp_c":21.8,"maxtemp_f":71.2,"mintemp_c":18.0,"mintemp_f":64.4,"avgtemp_c":19.5,"avgtemp_f":67.0,"maxwind_mph":16.3,"maxwind_kph":26.3,"totalprecip_mm":0.0,"totalprecip_in":0.0,"avgvis_km":19.7,"avgvis_miles":12.0,"avghumidity":72.0,"condition":{"text":"Partly cloudy","icon":"//cdn.apixu.com/weather/64x64/day/116.png","code":1003},"uv":5.6},"astro":{"sunrise":"06:41 AM","sunset":"05:20 PM","moonrise":"10:08 PM","moonset":"09:53 AM"}},{"date":"2019-01-26","date_epoch":1548460800,"day":{"maxtemp_c":20.5,"maxtemp_f":68.9,"mintemp_c":19.2,"mintemp_f":66.6,"avgtemp_c":19.2,"avgtemp_f":66.6,"maxwind_mph":11.9,"maxwind_kph":19.1,"totalprecip_mm":0.0,"totalprecip_in":0.0,"avgvis_km":19.7,"avgvis_miles":12.0,"avghumidity":86.0,"condition":{"text":"Partly cloudy","icon":"//cdn.apixu.com/weather/64x64/day/116.png","code":1003},"uv":5.8},"astro":{"sunrise":"06:40 AM","sunset":"05:21 PM","moonrise":"11:10 PM","moonset":"10:30 AM"}},{"date":"2019-01-27","date_epoch":1548547200,"day":{"maxtemp_c":23.7,"maxtemp_f":74.7,"mintemp_c":21.3,"mintemp_f":70.3,"avgtemp_c":20.9,"avgtemp_f":69.7,"maxwind_mph":25.7,"maxwind_kph":41.4,"totalprecip_mm":0.0,"totalprecip_in":0.0,"avgvis_km":19.7,"avgvis_miles":12.0,"avghumidity":65.0,"condition":{"text":"Partly cloudy","icon":"//cdn.apixu.com/weather/64x64/day/116.png","code":1003},"uv":3.8},"astro":{"sunrise":"06:40 AM","sunset":"05:22 PM","moonrise":"No moonrise","moonset":"11:08 AM"}},{"date":"2019-01-28","date_epoch":1548633600,"day":{"maxtemp_c":21.8,"maxtemp_f":71.2,"mintemp_c":16.2,"mintemp_f":61.2,"avgtemp_c":20.9,"avgtemp_f":69.7,"maxwind_mph":25.1,"maxwind_kph":40.3,"totalprecip_mm":4.6,"totalprecip_in":0.18,"avgvis_km":17.6,"avgvis_miles":10.0,"avghumidity":48.0,"condition":{"text":"Patchy rain possible","icon":"//cdn.apixu.com/weather/64x64/day/176.png","code":1063},"uv":5.0},"astro":{"sunrise":"06:40 AM","sunset":"05:23 PM","moonrise":"12:10 AM","moonset":"11:45 AM"}},{"date":"2019-01-29","date_epoch":1548720000,"day":{"maxtemp_c":20.1,"maxtemp_f":68.2,"mintemp_c":18.6,"mintemp_f":65.5,"avgtemp_c":18.3,"avgtemp_f":64.9,"maxwind_mph":15.2,"maxwind_kph":24.5,"totalprecip_mm":0.7,"totalprecip_in":0.03,"avgvis_km":17.5,"avgvis_miles":10.0,"avghumidity":55.0,"condition":{"text":"Patchy rain possible","icon":"//cdn.apixu.com/weather/64x64/day/176.png","code":1063},"uv":4.0},"astro":{"sunrise":"06:39 AM","sunset":"05:24 PM","moonrise":"01:09 AM","moonset":"12:23 PM"}}]}}

[v-bacao-msft · Accepted solution]

Hi @milind,

Forecastda is an array, and the dates inside are all corresponding to index.

You could use array[index] to arrange the elements in the array in the corresponding fields in order.

Like:

I used the data you provided, parsed JSON data, and got the data from the first day of the forecast.

Date: 

body('Parse_JSON')?['forecast']?['forecastday'][0]['date']

High temperature: 

body('Parse_JSON')?['forecast']?['forecastday'][0]['day']['maxtemp_c']

Low temperature: 

body('Parse_JSON')?['forecast']?['forecastday'][0]['day']['mintemp_c']

Image reference:

By analogy, to get the data for the next day, just change the index.

Please take a try.

Best Regards,

[tlevine]

Hi @v-bacao-msft  - how did you take the values from the variables and create the items for the sharepoint list?