# Data Structures

GeoPandas implements two main data structures, a `GeoSeries` and a `GeoDataFrame`. These are subclasses of pandas `Series` and `DataFrame`, respectively.

## GeoSeries

A `GeoSeries` is essentially a vector where each entry in the vector is a set of shapes corresponding to one observation. An entry may consist of only one shape (like a single polygon) or multiple shapes that are meant to be thought of as one observation (like the many polygons that make up the State of Hawaii or a country like Indonesia).

geopandas has three basic classes of geometric objects (which are actually shapely objects):

- Points / Multi-Points
- Lines / Multi-Lines
- Polygons / Multi-Polygons

Note that all entries in a `GeoSeries` need not be of the same geometric type, although certain export operations will fail if this is not the case.

### Overview of Attributes and Methods

The `GeoSeries` class implements nearly all of the attributes and methods of Shapely objects. When applied to a `GeoSeries`, they will apply elementwise to all geometries in the series. Binary operations can be applied between two `GeoSeries`, in which case the operation is carried out elementwise. The two series will be aligned by matching indices. Binary operations can also be applied to a single geometry, in which case the operation is carried out for each element of the series with that geometry. In either case, a `Series` or a `GeoSeries` will be returned, as appropriate.

A short summary of a few attributes and methods for GeoSeries is presented here, and a full list can be found in the all attributes and methods page. There is also a family of methods for creating new shapes by expanding existing shapes or applying set-theoretic operations like “union” described in geometric manipulations.

#### Attributes

- `area`: shape area (units of projection – see projections)
- `bounds`: tuple of max and min coordinates on each axis for each shape
- `total_bounds`: tuple of max and min coordinates on each axis for entire GeoSeries
- `geom_type`: type of geometry.
- `is_valid`: tests if coordinates make a shape that is reasonable geometric shape (according to this).

#### Basic Methods

- `distance(other)`: returns `Series` with minimum distance from each entry to `other`
- `centroid`: returns `GeoSeries` of centroids
- `representative_point()`: returns `GeoSeries` of points that are guaranteed to be within each geometry. It does NOT return centroids.
- `to_crs()`: change coordinate reference system. See projections
- `plot()`: plot `GeoSeries`. See mapping.

#### Relationship Tests

- `geom_almost_equals(other)`: is shape almost the same as `other` (good when floating point precision issues make shapes slightly different)
- `contains(other)`: is shape contained within `other`
- `intersects(other)`: does shape intersect `other`

## GeoDataFrame

A `GeoDataFrame` is a tabular data structure that contains a `GeoSeries`.

The most important property of a `GeoDataFrame` is that it always has one `GeoSeries` column that holds a special status. This `GeoSeries` is referred to as the `GeoDataFrame`’s “geometry”. When a spatial method is applied to a `GeoDataFrame` (or a spatial attribute like `area` is called), this commands will always act on the “geometry” column.

The “geometry” column – no matter its name – can be accessed through the `geometry` attribute (`gdf.geometry`), and the name of the `geometry` column can be found by typing `gdf.geometry.name`.

A `GeoDataFrame` may also contain other columns with geometrical (shapely) objects, but only one column can be the active geometry at a time. To change which column is the active geometry column, use the `set_geometry` method.

An example using the `worlds` GeoDataFrame:

    In [1]: world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))

    In [2]: world.head()
    Out[2]:
          pop_est      continent                  name iso_a3  gdp_md_est  \
    0  28400000.0           Asia           Afghanistan    AFG     22270.0
    1  12799293.0         Africa                Angola    AGO    110300.0
    2   3639453.0         Europe               Albania    ALB     21810.0
    3   4798491.0           Asia  United Arab Emirates    ARE    184300.0
    4  40913584.0  South America             Argentina    ARG    573900.0

                                                geometry
    0  POLYGON ((61.21081709172574 35.65007233330923,...
    1  (POLYGON ((16.32652835456705 -5.87747039146621...
    2  POLYGON ((20.59024743010491 41.85540416113361,...
    3  POLYGON ((51.57951867046327 24.24549713795111,...
    4  (POLYGON ((-65.50000000000003 -55.199999999999...

    #Plot countries
    In [3]: world.plot();

Currently, the column named “geometry” with country borders is the active geometry column:

    In [4]: world.geometry.name
    Out[4]: 'geometry'

We can also rename this column to “borders”:

    In [5]: world = world.rename(columns={'geometry': 'borders'}).set_geometry('borders')

    In [6]: world.geometry.name
    Out[6]: 'borders'

Now, we create centroids and make it the geometry:

    In [7]: world['centroid_column'] = world.centroid

    In [8]: world = world.set_geometry('centroid_column')

    In [9]: world.plot();

Note: A `GeoDataFrame` keeps track of the active column by name, so if you rename the active geometry column, you must also reset the geometry:

    gdf = gdf.rename(columns={'old_name': 'new_name'}).set_geometry('new_name')

Note 2: Somewhat confusingly, by default when you use the `read_file` command, the column containing spatial objects from the file is named “geometry” by default, and will be set as the active geometry column. However, despite using the same term for the name of the column and the name of the special attribute that keeps track of the active column, they are distinct. You can easily shift the active geometry column to a different `GeoSeries` with the `set_geometry` command. Further, `gdf.geometry` will always return the active geometry column, not the column named `geometry`. If you wish to call a column named “geometry”, and a different column is the active geometry column, use `gdf['geometry']`, not `gdf.geometry`.

### Attributes and Methods

Any of the attributes calls or methods described for a `GeoSeries` will work on a `GeoDataFrame` – effectively, they are just applied to the “geometry” `GeoSeries`.

However, `GeoDataFrames` also have a few extra methods for input and output which are described on the Input and Output page and for geocoding with are described in Geocoding.