ee.FeatureCollection.flatten

 // Counties in New Mexico, USA. 
 var 
  
 counties 
  
 = 
  
 ee 
 . 
 FeatureCollection 
 ( 
 'TIGER/2018/Counties' 
 ) 
  
 . 
 filter 
 ( 
 'STATEFP == "35"' 
 ); 
 // Monthly climate and climatic water balance surfaces for January 2020. 
 var 
  
 climate 
  
 = 
  
 ee 
 . 
 ImageCollection 
 ( 
 'IDAHO_EPSCOR/TERRACLIMATE' 
 ) 
  
 . 
 filterDate 
 ( 
 '2020-01' 
 , 
  
 '2020-02' 
 ); 
 // Calculate mean climate variables for each county per climate surface 
 // time step. The result is a FeatureCollection of FeatureCollections. 
 var 
  
 countiesClimate 
  
 = 
  
 climate 
 . 
 map 
 ( 
 function 
 ( 
 image 
 ) 
  
 { 
  
 return 
  
 image 
 . 
 reduceRegions 
 ({ 
  
 collection 
 : 
  
 counties 
 , 
  
 reducer 
 : 
  
 ee 
 . 
 Reducer 
 . 
 mean 
 (), 
  
 scale 
 : 
  
 5000 
 , 
  
 crs 
 : 
  
 'EPSG:4326' 
  
 }); 
 }); 
 // Note that a printed FeatureCollection of FeatureCollections is not 
 // recursively expanded, you cannot view metadata of the features within the 
 // nested collections until you isolate a single collection or flatten the 
 // collections. 
 print 
 ( 
 'FeatureCollection of FeatureCollections' 
 , 
  
 countiesClimate 
 ); 
 print 
 ( 
 'Flattened FeatureCollection of FeatureCollections' 
 , 
  
 countiesClimate 
 . 
 flatten 
 ()); 

 # Counties in New Mexico, USA. 
 counties 
 = 
 ee 
 . 
 FeatureCollection 
 ( 
 'TIGER/2018/Counties' 
 ) 
 . 
 filter 
 ( 
 'STATEFP == "35"' 
 ) 
 # Monthly climate and climatic water balance surfaces for January 2020. 
 climate 
 = 
 ee 
 . 
 ImageCollection 
 ( 
 'IDAHO_EPSCOR/TERRACLIMATE' 
 ) 
 . 
 filterDate 
 ( 
 '2020-01' 
 , 
 '2020-02' 
 ) 
 # Calculate mean climate variables for each county per climate surface 
 # time step. The result is a FeatureCollection of FeatureCollections. 
 def 
  
 reduce_mean 
 ( 
 image 
 ): 
 return 
 image 
 . 
 reduceRegions 
 ( 
 ** 
 { 
 'collection' 
 : 
 counties 
 , 
 'reducer' 
 : 
 ee 
 . 
 Reducer 
 . 
 mean 
 (), 
 'scale' 
 : 
 5000 
 , 
 'crs' 
 : 
 'EPSG:4326' 
 }) 
 counties_climate 
 = 
 climate 
 . 
 map 
 ( 
 reduce_mean 
 ) 
 # Note that a printed FeatureCollection of FeatureCollections is not 
 # recursively expanded, you cannot view metadata of the features within the 
 # nested collections until you isolate a single collection or flatten the 
 # collections. 
 print 
 ( 
 'FeatureCollection of FeatureCollections:' 
 , 
 counties_climate 
 . 
 getInfo 
 ()) 
 print 
 ( 
 'Flattened FeatureCollection of FeatureCollections:' 
 , 
 counties_climate 
 . 
 flatten 
 () 
 . 
 getInfo 
 ())