geopandas.GeoSeries

class geopandas.GeoSeries(data=None, index=None, crs=None, **kwargs)

A Series object designed to store shapely geometry objects.

Parameters

dataarray-like, dict, scalar value

The geometries to store in the GeoSeries.

indexarray-like or Index

The index for the GeoSeries.

crsvalue (optional)

Coordinate Reference System of the geometry objects. Can be anything accepted by pyproj.CRS.from_user_input(), such as an authority string (eg “EPSG:4326”) or a WKT string.

kwargs

Additional arguments passed to the Series constructor,

e.g. name.

See also

GeoDataFrame

pandas.Series

Examples

>>> from shapely.geometry import Point
>>> s = geopandas.GeoSeries([Point(1, 1), Point(2, 2), Point(3, 3)])
>>> s
0    POINT (1.00000 1.00000)
1    POINT (2.00000 2.00000)
2    POINT (3.00000 3.00000)
dtype: geometry

>>> s = geopandas.GeoSeries(
...     [Point(1, 1), Point(2, 2), Point(3, 3)], crs="EPSG:3857"
... )
>>> s.crs  
<Projected CRS: EPSG:3857>
Name: WGS 84 / Pseudo-Mercator
Axis Info [cartesian]:
- X[east]: Easting (metre)
- Y[north]: Northing (metre)
Area of Use:
- name: World - 85°S to 85°N
- bounds: (-180.0, -85.06, 180.0, 85.06)
Coordinate Operation:
- name: Popular Visualisation Pseudo-Mercator
- method: Popular Visualisation Pseudo Mercator
Datum: World Geodetic System 1984
- Ellipsoid: WGS 84
- Prime Meridian: Greenwich

>>> s = geopandas.GeoSeries(
...    [Point(1, 1), Point(2, 2), Point(3, 3)], index=["a", "b", "c"], crs=4326
... )
>>> s
a    POINT (1.00000 1.00000)
b    POINT (2.00000 2.00000)
c    POINT (3.00000 3.00000)
dtype: geometry

>>> s.crs
<Geographic 2D CRS: EPSG:4326>
Name: WGS 84
Axis Info [ellipsoidal]:
- Lat[north]: Geodetic latitude (degree)
- Lon[east]: Geodetic longitude (degree)
Area of Use:
- name: World.
- bounds: (-180.0, -90.0, 180.0, 90.0)
Datum: World Geodetic System 1984 ensemble
- Ellipsoid: WGS 84
- Prime Meridian: Greenwich

__init__(*args, **kwargs)

Methods

__init__(*args, **kwargs)
abs()	Return a Series/DataFrame with absolute numeric value of each element.
add(other[, level, fill_value, axis])	Return Addition of series and other, element-wise (binary operator add).
add_prefix(prefix)	Prefix labels with string prefix.
add_suffix(suffix)	Suffix labels with string suffix.
affine_transform(matrix)	Return a GeoSeries with translated geometries.
agg([func, axis])	Aggregate using one or more operations over the specified axis.
aggregate([func, axis])	Aggregate using one or more operations over the specified axis.
align(other[, join, axis, level, copy, ...])	Align two objects on their axes with the specified join method.
all([axis, bool_only, skipna, level])	Return whether all elements are True, potentially over an axis.
any([axis, bool_only, skipna, level])	Return whether any element is True, potentially over an axis.
append(*args, **kwargs)	Concatenate two or more Series.
apply(func[, convert_dtype, args])	One-dimensional ndarray with axis labels (including time series).
argmax([axis, skipna])	Return int position of the largest value in the Series.
argmin([axis, skipna])	Return int position of the smallest value in the Series.
argsort([axis, kind, order])	Return the integer indices that would sort the Series values.
asfreq(freq[, method, how, normalize, ...])	Convert time series to specified frequency.
asof(where[, subset])	Return the last row(s) without any NaNs before where.
astype(dtype[, copy, errors])	Cast a pandas object to a specified dtype dtype.
at_time(time[, asof, axis])	Select values at particular time of day (e.g., 9:30AM).
autocorr([lag])	Compute the lag-N autocorrelation.
backfill([axis, inplace, limit, downcast])	Synonym for DataFrame.fillna() with method='bfill'.
between(left, right[, inclusive])	Return boolean Series equivalent to left <= series <= right.
between_time(start_time, end_time[, ...])	Select values between particular times of the day (e.g., 9:00-9:30 AM).
bfill([axis, inplace, limit, downcast])	Synonym for DataFrame.fillna() with method='bfill'.
bool()	Return the bool of a single element Series or DataFrame.
buffer(distance[, resolution])	Returns a GeoSeries of geometries representing all points within a given distance of each geometric object.
clip(mask[, keep_geom_type])	Clip points, lines, or polygon geometries to the mask extent.
combine(other, func[, fill_value])	Combine the Series with a Series or scalar according to func.
combine_first(other)	Update null elements with value in the same location in 'other'.
compare(other[, align_axis, keep_shape, ...])	Compare to another Series and show the differences.
contains(other[, align])	Returns a Series of dtype('bool') with value True for each aligned geometry that contains other.
convert_dtypes([infer_objects, ...])	Convert columns to best possible dtypes using dtypes supporting pd.NA.
copy([deep])	Make a copy of this object's indices and data.
corr(other[, method, min_periods])	Compute correlation with other Series, excluding missing values.
count([level])	Return number of non-NA/null observations in the Series.
cov(other[, min_periods, ddof])	Compute covariance with Series, excluding missing values.
covered_by(other[, align])	Returns a Series of dtype('bool') with value True for each aligned geometry that is entirely covered by other.
covers(other[, align])	Returns a Series of dtype('bool') with value True for each aligned geometry that is entirely covering other.
crosses(other[, align])	Returns a Series of dtype('bool') with value True for each aligned geometry that cross other.
cummax([axis, skipna])	Return cumulative maximum over a DataFrame or Series axis.
cummin([axis, skipna])	Return cumulative minimum over a DataFrame or Series axis.
cumprod([axis, skipna])	Return cumulative product over a DataFrame or Series axis.
cumsum([axis, skipna])	Return cumulative sum over a DataFrame or Series axis.
describe([percentiles, include, exclude, ...])	Generate descriptive statistics.
diff([periods])	First discrete difference of element.
difference(other[, align])	Returns a GeoSeries of the points in each aligned geometry that are not in other.
disjoint(other[, align])	Returns a Series of dtype('bool') with value True for each aligned geometry disjoint to other.
distance(other[, align])	Returns a Series containing the distance to aligned other.
div(other[, level, fill_value, axis])	Return Floating division of series and other, element-wise (binary operator truediv).
divide(other[, level, fill_value, axis])	Return Floating division of series and other, element-wise (binary operator truediv).
divmod(other[, level, fill_value, axis])	Return Integer division and modulo of series and other, element-wise (binary operator divmod).
dot(other)	Compute the dot product between the Series and the columns of other.
drop([labels, axis, index, columns, level, ...])	Return Series with specified index labels removed.
drop_duplicates([keep, inplace])	Return Series with duplicate values removed.
droplevel(level[, axis])	Return Series/DataFrame with requested index / column level(s) removed.
dropna([axis, inplace, how])	Return a new Series with missing values removed.
duplicated([keep])	Indicate duplicate Series values.
eq(other[, level, fill_value, axis])	Return Equal to of series and other, element-wise (binary operator eq).
equals(other)	Test whether two objects contain the same elements.
estimate_utm_crs([datum_name])	Returns the estimated UTM CRS based on the bounds of the dataset.
ewm([com, span, halflife, alpha, ...])	Provide exponential weighted (EW) functions.
expanding([min_periods, center, axis, method])	Provide expanding transformations.
explode([ignore_index, index_parts])	Explode multi-part geometries into multiple single geometries.
explore(*args, **kwargs)	Interactive map based on folium/leaflet.jsInteractive map based on GeoPandas and folium/leaflet.js
factorize([sort, na_sentinel])	Encode the object as an enumerated type or categorical variable.
ffill([axis, inplace, limit, downcast])	Synonym for DataFrame.fillna() with method='ffill'.
fillna([value, method, inplace])	Fill NA values with a geometry (empty polygon by default).
filter([items, like, regex, axis])	Subset the dataframe rows or columns according to the specified index labels.
first(offset)	Select initial periods of time series data based on a date offset.
first_valid_index()	Return index for first non-NA value or None, if no NA value is found.
floordiv(other[, level, fill_value, axis])	Return Integer division of series and other, element-wise (binary operator floordiv).
from_file(filename, **kwargs)	Alternate constructor to create a GeoSeries from a file.
from_wkb(data[, index, crs])	Alternate constructor to create a GeoSeries from a list or array of WKB objects
from_wkt(data[, index, crs])	Alternate constructor to create a GeoSeries from a list or array of WKT objects
from_xy(x, y[, z, index, crs])	Alternate constructor to create a GeoSeries of Point geometries from lists or arrays of x, y(, z) coordinates
ge(other[, level, fill_value, axis])	Return Greater than or equal to of series and other, element-wise (binary operator ge).
geom_almost_equals(other[, decimal, align])	Returns a Series of dtype('bool') with value True if each aligned geometry is approximately equal to other.
geom_equals(other[, align])	Returns a Series of dtype('bool') with value True for each aligned geometry equal to other.
geom_equals_exact(other, tolerance[, align])	Return True for all geometries that equal aligned other to a given tolerance, else False.
get(key[, default])	Get item from object for given key (ex: DataFrame column).
groupby([by, axis, level, as_index, sort, ...])	Group Series using a mapper or by a Series of columns.
gt(other[, level, fill_value, axis])	Return Greater than of series and other, element-wise (binary operator gt).
head([n])	Return the first n rows.
hist([by, ax, grid, xlabelsize, xrot, ...])	Draw histogram of the input series using matplotlib.
idxmax([axis, skipna])	Return the row label of the maximum value.
idxmin([axis, skipna])	Return the row label of the minimum value.
infer_objects()	Attempt to infer better dtypes for object columns.
interpolate(distance[, normalized])	Return a point at the specified distance along each geometry
intersection(other[, align])	Returns a GeoSeries of the intersection of points in each aligned geometry with other.
intersects(other[, align])	Returns a Series of dtype('bool') with value True for each aligned geometry that intersects other.
isin(values)	Whether elements in Series are contained in values.
isna()	Detect missing values.
isnull()	Alias for isna method.
item()	Return the first element of the underlying data as a Python scalar.
items()	Lazily iterate over (index, value) tuples.
iteritems()	Lazily iterate over (index, value) tuples.
keys()	Return alias for index.
kurt([axis, skipna, level, numeric_only])	Return unbiased kurtosis over requested axis.
kurtosis([axis, skipna, level, numeric_only])	Return unbiased kurtosis over requested axis.
last(offset)	Select final periods of time series data based on a date offset.
last_valid_index()	Return index for last non-NA value or None, if no NA value is found.
le(other[, level, fill_value, axis])	Return Less than or equal to of series and other, element-wise (binary operator le).
lt(other[, level, fill_value, axis])	Return Less than of series and other, element-wise (binary operator lt).
mad([axis, skipna, level])	Return the mean absolute deviation of the values over the requested axis.
map(arg[, na_action])	Map values of Series according to input correspondence.
mask(cond[, other, inplace, axis, level, ...])	Replace values where the condition is True.
max([axis, skipna, level, numeric_only])	Return the maximum of the values over the requested axis.
mean([axis, skipna, level, numeric_only])	Return the mean of the values over the requested axis.
median([axis, skipna, level, numeric_only])	Return the median of the values over the requested axis.
memory_usage([index, deep])	Return the memory usage of the Series.
min([axis, skipna, level, numeric_only])	Return the minimum of the values over the requested axis.
mod(other[, level, fill_value, axis])	Return Modulo of series and other, element-wise (binary operator mod).
mode([dropna])	Return the mode(s) of the Series.
mul(other[, level, fill_value, axis])	Return Multiplication of series and other, element-wise (binary operator mul).
multiply(other[, level, fill_value, axis])	Return Multiplication of series and other, element-wise (binary operator mul).
ne(other[, level, fill_value, axis])	Return Not equal to of series and other, element-wise (binary operator ne).
nlargest([n, keep])	Return the largest n elements.
notna()	Detect non-missing values.
notnull()	Alias for notna method.
nsmallest([n, keep])	Return the smallest n elements.
nunique([dropna])	Return number of unique elements in the object.
overlaps(other[, align])	Returns True for all aligned geometries that overlap other, else False.
pad([axis, inplace, limit, downcast])	Synonym for DataFrame.fillna() with method='ffill'.
pct_change([periods, fill_method, limit, freq])	Percentage change between the current and a prior element.
pipe(func, *args, **kwargs)	Apply func(self, *args, **kwargs).
plot(*args, **kwargs)	Plot a GeoSeries.
pop(item)	Return item and drops from series.
pow(other[, level, fill_value, axis])	Return Exponential power of series and other, element-wise (binary operator pow).
prod([axis, skipna, level, numeric_only, ...])	Return the product of the values over the requested axis.
product([axis, skipna, level, numeric_only, ...])	Return the product of the values over the requested axis.
project(other[, normalized, align])	Return the distance along each geometry nearest to other
quantile([q, interpolation])	Return value at the given quantile.
radd(other[, level, fill_value, axis])	Return Addition of series and other, element-wise (binary operator radd).
rank([axis, method, numeric_only, ...])	Compute numerical data ranks (1 through n) along axis.
ravel([order])	Return the flattened underlying data as an ndarray.
rdiv(other[, level, fill_value, axis])	Return Floating division of series and other, element-wise (binary operator rtruediv).
rdivmod(other[, level, fill_value, axis])	Return Integer division and modulo of series and other, element-wise (binary operator rdivmod).
reindex([index])	Conform Series to new index with optional filling logic.
reindex_like(other[, method, copy, limit, ...])	Return an object with matching indices as other object.
relate(other[, align])	Returns the DE-9IM intersection matrices for the geometries
rename([index, axis, copy, inplace, level, ...])	Alter Series index labels or name.
rename_axis([mapper, index, columns, axis, ...])	Set the name of the axis for the index or columns.
reorder_levels(order)	Rearrange index levels using input order.
repeat(repeats[, axis])	Repeat elements of a Series.
replace([to_replace, value, inplace, limit, ...])	Replace values given in to_replace with value.
representative_point()	Returns a GeoSeries of (cheaply computed) points that are guaranteed to be within each geometry.
resample(rule[, axis, closed, label, ...])	Resample time-series data.
reset_index([level, drop, name, inplace])	Generate a new DataFrame or Series with the index reset.
rfloordiv(other[, level, fill_value, axis])	Return Integer division of series and other, element-wise (binary operator rfloordiv).
rmod(other[, level, fill_value, axis])	Return Modulo of series and other, element-wise (binary operator rmod).
rmul(other[, level, fill_value, axis])	Return Multiplication of series and other, element-wise (binary operator rmul).
rolling(window[, min_periods, center, ...])	Provide rolling window calculations.
rotate(angle[, origin, use_radians])	Returns a GeoSeries with rotated geometries.
round([decimals])	Round each value in a Series to the given number of decimals.
rpow(other[, level, fill_value, axis])	Return Exponential power of series and other, element-wise (binary operator rpow).
rsub(other[, level, fill_value, axis])	Return Subtraction of series and other, element-wise (binary operator rsub).
rtruediv(other[, level, fill_value, axis])	Return Floating division of series and other, element-wise (binary operator rtruediv).
sample([n, frac, replace, weights, ...])	Return a random sample of items from an axis of object.
scale([xfact, yfact, zfact, origin])	Returns a GeoSeries with scaled geometries.
searchsorted(value[, side, sorter])	Find indices where elements should be inserted to maintain order.
select(*args, **kwargs)	One-dimensional ndarray with axis labels (including time series).
sem([axis, skipna, level, ddof, numeric_only])	Return unbiased standard error of the mean over requested axis.
set_axis(labels[, axis, inplace])	Assign desired index to given axis.
set_crs([crs, epsg, inplace, allow_override])	Set the Coordinate Reference System (CRS) of a GeoSeries.
set_flags(*[, copy, allows_duplicate_labels])	Return a new object with updated flags.
shift([periods, freq, axis, fill_value])	Shift index by desired number of periods with an optional time freq.
simplify(*args, **kwargs)	Returns a GeoSeries containing a simplified representation of each geometry.
skew([xs, ys, origin, use_radians])	Returns a GeoSeries with skewed geometries.
slice_shift([periods, axis])	Equivalent to shift without copying data.
sort_index(*args, **kwargs)	One-dimensional ndarray with axis labels (including time series).
sort_values([axis, ascending, inplace, ...])	Sort by the values.
squeeze([axis])	Squeeze 1 dimensional axis objects into scalars.
std([axis, skipna, level, ddof, numeric_only])	Return sample standard deviation over requested axis.
sub(other[, level, fill_value, axis])	Return Subtraction of series and other, element-wise (binary operator sub).
subtract(other[, level, fill_value, axis])	Return Subtraction of series and other, element-wise (binary operator sub).
sum([axis, skipna, level, numeric_only, ...])	Return the sum of the values over the requested axis.
swapaxes(axis1, axis2[, copy])	Interchange axes and swap values axes appropriately.
swaplevel([i, j, copy])	Swap levels i and j in a MultiIndex.
symmetric_difference(other[, align])	Returns a GeoSeries of the symmetric difference of points in each aligned geometry with other.
tail([n])	Return the last n rows.
take(*args, **kwargs)	One-dimensional ndarray with axis labels (including time series).
to_clipboard([excel, sep])	Copy object to the system clipboard.
to_crs([crs, epsg])	Returns a GeoSeries with all geometries transformed to a new coordinate reference system.
to_csv([path_or_buf, sep, na_rep, ...])	Write object to a comma-separated values (csv) file.
to_dict([into])	Convert Series to {label -> value} dict or dict-like object.
to_excel(excel_writer[, sheet_name, na_rep, ...])	Write object to an Excel sheet.
to_file(filename[, driver, index])	Write the GeoSeries to a file.
to_frame([name])	Convert Series to DataFrame.
to_hdf(path_or_buf, key[, mode, complevel, ...])	Write the contained data to an HDF5 file using HDFStore.
to_json(**kwargs)	Returns a GeoJSON string representation of the GeoSeries.
to_latex([buf, columns, col_space, header, ...])	Render object to a LaTeX tabular, longtable, or nested table/tabular.
to_list()	Return a list of the values.
to_markdown([buf, mode, index, storage_options])	Print Series in Markdown-friendly format.
to_numpy([dtype, copy, na_value])	A NumPy ndarray representing the values in this Series or Index.
to_period([freq, copy])	Convert Series from DatetimeIndex to PeriodIndex.
to_pickle(path[, compression, protocol, ...])	Pickle (serialize) object to file.
to_sql(name, con[, schema, if_exists, ...])	Write records stored in a DataFrame to a SQL database.
to_string([buf, na_rep, float_format, ...])	Render a string representation of the Series.
to_timestamp([freq, how, copy])	Cast to DatetimeIndex of Timestamps, at beginning of period.
to_wkb([hex])	Convert GeoSeries geometries to WKB
to_wkt(**kwargs)	Convert GeoSeries geometries to WKT
to_xarray()	Return an xarray object from the pandas object.
tolist()	Return a list of the values.
touches(other[, align])	Returns a Series of dtype('bool') with value True for each aligned geometry that touches other.
transform(func[, axis])	Call func on self producing a Series with transformed values.
translate([xoff, yoff, zoff])	Returns a GeoSeries with translated geometries.
transpose(*args, **kwargs)	Return the transpose, which is by definition self.
truediv(other[, level, fill_value, axis])	Return Floating division of series and other, element-wise (binary operator truediv).
truncate([before, after, axis, copy])	Truncate a Series or DataFrame before and after some index value.
tshift([periods, freq, axis])	Shift the time index, using the index's frequency if available.
tz_convert(tz[, axis, level, copy])	Convert tz-aware axis to target time zone.
tz_localize(tz[, axis, level, copy, ...])	Localize tz-naive index of a Series or DataFrame to target time zone.
union(other[, align])	Returns a GeoSeries of the union of points in each aligned geometry with other.
unique()	Return unique values of Series object.
unstack([level, fill_value])	Unstack, also known as pivot, Series with MultiIndex to produce DataFrame.
update(other)	Modify Series in place using values from passed Series.
value_counts([normalize, sort, ascending, ...])	Return a Series containing counts of unique values.
var([axis, skipna, level, ddof, numeric_only])	Return unbiased variance over requested axis.
view([dtype])	Create a new view of the Series.
where(cond[, other, inplace, axis, level, ...])	Replace values where the condition is False.
within(other[, align])	Returns a Series of dtype('bool') with value True for each aligned geometry that is within other.
xs(key[, axis, level, drop_level])	Return cross-section from the Series/DataFrame.

Attributes

T	Return the transpose, which is by definition self.
area	Returns a Series containing the area of each geometry in the GeoSeries expressed in the units of the CRS.
array	The ExtensionArray of the data backing this Series or Index.
at	Access a single value for a row/column label pair.
attrs	Dictionary of global attributes of this dataset.
axes	Return a list of the row axis labels.
boundary	Returns a GeoSeries of lower dimensional objects representing each geometries's set-theoretic boundary.
bounds	Returns a DataFrame with columns minx, miny, maxx, maxy values containing the bounds for each geometry.
cascaded_union	Deprecated: use unary_union instead
centroid	Returns a GeoSeries of points representing the centroid of each geometry.
convex_hull	Returns a GeoSeries of geometries representing the convex hull of each geometry.
crs	The Coordinate Reference System (CRS) represented as a pyproj.CRS object.
cx	Coordinate based indexer to select by intersection with bounding box.
dtype	Return the dtype object of the underlying data.
dtypes	Return the dtype object of the underlying data.
empty	Indicator whether DataFrame is empty.
envelope	Returns a GeoSeries of geometries representing the envelope of each geometry.
exterior	Returns a GeoSeries of LinearRings representing the outer boundary of each polygon in the GeoSeries.
flags	Get the properties associated with this pandas object.
geom_type	Returns a Series of strings specifying the Geometry Type of each object.
geometry
has_sindex	Check the existence of the spatial index without generating it.
has_z	Returns a Series of dtype('bool') with value True for features that have a z-component.
hasnans	Return if I have any nans; enables various perf speedups.
iat	Access a single value for a row/column pair by integer position.
iloc	Purely integer-location based indexing for selection by position.
index	The index (axis labels) of the Series.
interiors	Returns a Series of List representing the inner rings of each polygon in the GeoSeries.
is_empty	Returns a Series of dtype('bool') with value True for empty geometries.
is_monotonic	Return boolean if values in the object are monotonic_increasing.
is_monotonic_decreasing	Return boolean if values in the object are monotonic_decreasing.
is_monotonic_increasing	Alias for is_monotonic.
is_ring	Returns a Series of dtype('bool') with value True for features that are closed.
is_simple	Returns a Series of dtype('bool') with value True for geometries that do not cross themselves.
is_unique	Return boolean if values in the object are unique.
is_valid	Returns a Series of dtype('bool') with value True for geometries that are valid.
length	Returns a Series containing the length of each geometry expressed in the units of the CRS.
loc	Access a group of rows and columns by label(s) or a boolean array.
name	Return the name of the Series.
nbytes	Return the number of bytes in the underlying data.
ndim	Number of dimensions of the underlying data, by definition 1.
shape	Return a tuple of the shape of the underlying data.
sindex	Generate the spatial index
size	Return the number of elements in the underlying data.
total_bounds	Returns a tuple containing minx, miny, maxx, maxy values for the bounds of the series as a whole.
type	Return the geometry type of each geometry in the GeoSeries
unary_union	Returns a geometry containing the union of all geometries in the GeoSeries.
values	Return Series as ndarray or ndarray-like depending on the dtype.
x	Return the x location of point geometries in a GeoSeries
y	Return the y location of point geometries in a GeoSeries
z	Return the z location of point geometries in a GeoSeries

GeoSeries geopandas.GeoSeries.area