Spatial overlays allow you to compare two GeoDataFrames containing polygon or multipolygon geometries
and create a new GeoDataFrame with the new geometries representing the spatial combination *and*
merged properties. This allows you to answer questions like

What are the demographics of the census tracts within 1000 ft of the highway?

The basic idea is demonstrated by the graphic below but keep in mind that overlays operate at the dataframe level, not on individual geometries, and the properties from both are retained

Now we can load up two GeoDataFrames containing (multi)polygon geometries...

In [ ]:

```
%matplotlib inline
from shapely.geometry import Point
from geopandas import GeoDataFrame, read_file
from geopandas.tools import overlay
from geodatasets import get_path
# NYC Boros
zippath = get_path("nybb")
polydf = read_file(zippath)
# Generate some circles
b = [int(x) for x in polydf.total_bounds]
N = 10
polydf2 = GeoDataFrame(
[
{"geometry": Point(x, y).buffer(10000), "value1": x + y, "value2": x - y}
for x, y in zip(
range(b[0], b[2], int((b[2] - b[0]) / N)),
range(b[1], b[3], int((b[3] - b[1]) / N)),
)
]
)
```

The first dataframe contains multipolygons of the NYC boros

In [ ]:

```
polydf.plot()
```

In [ ]:

```
polydf2.plot(cmap="tab20b")
```

The `geopandas.tools.overlay`

function takes three arguments:

- df1
- df2
- how

Where `how`

can be one of:

```
['intersection',
'union',
'identity',
'symmetric_difference',
'difference']
```

So let's identify the areas (and attributes) where both dataframes intersect using the `overlay`

method.

In [ ]:

```
newdf = polydf.overlay(polydf2, how="intersection")
newdf.plot(cmap="tab20b")
```

In [ ]:

```
polydf.head()
```

In [ ]:

```
polydf2.head()
```

In [ ]:

```
newdf.head()
```

Now let's look at the other `how`

operations:

In [ ]:

```
newdf = polydf.overlay(polydf2, how="union")
newdf.plot(cmap="tab20b")
```

In [ ]:

```
newdf = polydf.overlay(polydf2, how="identity")
newdf.plot(cmap="tab20b")
```

In [ ]:

```
newdf = polydf.overlay(polydf2, how="symmetric_difference")
newdf.plot(cmap="tab20b")
```

In [ ]:

```
newdf = polydf.overlay(polydf2, how="difference")
newdf.plot(cmap="tab20b")
```