var L8 = ee.ImageCollection("LANDSAT/LC08/C01/T1_TOA")
.filterDate('2016-06-01', '2016-07-31') // you can change date here
.filter(ee.Filter.lt("CLOUD_COVER", 0.75))
.filterBounds(collection[i])
.map(maskLandsatclouds)
.sort('DATE_ACQUIRED')
.select(L8bands)

 var count = L8.size();
 for (var j=0;j< 10 ;j++){
 // Get the number of images.
 print(j);

var mosaic_L8 =L8.median().clip(collection[i]); // here we are taking the
 median at each pixel in the collection
 Map.addLayer(mosaic_L8, L8vis, "mosaic_L8")

// Create an NDWI image, define visualization parameters and display.
 var ndwi = mosaic_L8.normalizedDifference(['B3', 'B5']);

 var ndwiViz = {min: 0.5, max: 1, palette: ['44c9f1', '1637f1']};
 //Map.addLayer(ndwi, ndwiViz, 'NDWI', false);

 // Mask the non-watery parts of the image, where NDWI < 0.10.
 var ndwiMasked = ndwi.updateMask(ndwi.gte(0.10));
 Map.addLayer(ndwiMasked, ndwiViz,'NDWI masked '+ ee.Number(j).getInfo());

 Map.centerObject(ndwiMasked);

// // NDWI expression
var ndwiL8 = mosaic_L8.expression(
'(G - NIR) / (G + NIR)' , {
'NIR' : mosaic_L8.select('B5'),
'G' : mosaic_L8.select('B3')
} ) ;

// NDWI math operation
var ndwi_L8 = mosaic_L8.select('B3').subtract(mosaic_L8.select('B5'))
.divide(mosaic_L8.select('B3').add(mosaic_L8.select('B5')));