# Statistics of Image Regions

To get image statistics in multiple regions stored in a `FeatureCollection`,
you can use `image.reduceRegions()` to reduce multiple regions at once.
The input to `reduceRegions()` is an `Image` and a
`FeatureCollection`. The output is another `FeatureCollection`
with the `reduceRegions()` output set as properties on each `Feature`.
In this example, means of the Landsat 7 annual composite bands in each feature geometry
will be added as properties to the input features:

### Code Editor (JavaScript)

```javascript
// Load input imagery: Landsat 7 5-year composite.
var image = ee.Image('LANDSAT/LE7_TOA_5YEAR/2008_2012');

// Load a FeatureCollection of counties in Maine.
var maineCounties = ee.FeatureCollection('TIGER/2016/Counties')
  .filter(ee.Filter.eq('STATEFP', '23'));

// Add reducer output to the Features in the collection.
var maineMeansFeatures = image.reduceRegions({
  collection: maineCounties,
  reducer: ee.Reducer.mean(),
  scale: 30,
});

// Print the first feature, to illustrate the result.
print(ee.Feature(maineMeansFeatures.first()).select(image.bandNames()));
```
Python setup

See the [Python Environment](https://developers.google.com/earth-engine/guides/python_install) page for information on the Python API and using
`geemap` for interactive development.

```python
import ee
import geemap.core as geemap
```

### Colab (Python)

```python
# Load input imagery: Landsat 7 5-year composite.
image = ee.Image('LANDSAT/LE7_TOA_5YEAR/2008_2012')

# Load a FeatureCollection of counties in Maine.
maine_counties = ee.FeatureCollection('TIGER/2016/Counties').filter(
    ee.Filter.eq('STATEFP', '23')
)

# Add reducer output to the Features in the collection.
maine_means_features = image.reduceRegions(
    collection=maine_counties, reducer=ee.Reducer.mean(), scale=30
)

# Print the first feature, to illustrate the result.
display(ee.Feature(maine_means_features.first()).select(image.bandNames()))
```

Observe that new properties, keyed by band name, have been added to the
`FeatureCollection` to store the mean of the composite in each
`Feature` geometry. As a result, the output of the print statement should
look something like:

```
Feature (Polygon, 7 properties)
  type: Feature
  geometry: Polygon, 7864 vertices
  properties: Object (7 properties)
    B1: 24.034822192925134
    B2: 19.40202233717122
    B3: 13.568454303016292
    B4: 63.00423784301736
    B5: 29.142707062821305
    B6_VCID_2: 186.18172376827042
    B7: 12.064469664746415
    
```