starepandas.STAREDataFrame

class STAREDataFrame(*args, sids=None, add_sids=False, level=None, trixels=None, add_trixels=False, n_partitions=1, **kwargs)

__init__(*args, sids=None, add_sids=False, level=None, trixels=None, add_trixels=False, n_partitions=1, **kwargs)

A STAREDataFrame object is a pandas.DataFrame that has a special column with STARE indices and optionally a special column holding the trixel representation. In addition to the standard DataFrame constructor arguments, STARE also accepts the following keyword arguments:

Parameters:

sidsstr or array-like

If str, column to use as stare column. If array, will be set as ‘stare’ column on STAREDataFrame.

add_sidsbool

If true, STARE index values will be generated using a geometry column

level: int

If add_stare is True, then use level as the maximum STARE level

trixelsstr or array-like

If str, column to use as trixel column. If array, will be set as ‘trixel’ column on STAREDataFrame.

add_trixelsbool

If true, trixels will be generated from the STARE column.

Examples

>>> cities = ['Buenos Aires', 'Brasilia', 'Santiago', 'Bogota', 'Caracas']
>>> latitudes = [-34.58, -15.78, -33.45, 4.60, 10.48]
>>> longitudes = [-58.66, -47.91, -70.66, -74.08, -66.86]
>>> data =  {'City': cities, 'Latitude': latitudes, 'Longitude': longitudes}
>>> sids = starepandas.sids_from_xy(longitudes, latitudes, level=5)
>>> sdf = starepandas.STAREDataFrame(data, sids=sids)

Methods

__init__(*args[, sids, add_sids, level, ...])	A STAREDataFrame object is a pandas.DataFrame that has a special column with STARE indices and optionally a special column holding the trixel representation.
abs()	Return a Series/DataFrame with absolute numeric value of each element.
add(other[, axis, level, fill_value])	Get Addition of dataframe and other, element-wise (binary operator add).
add_prefix(prefix[, axis])	Prefix labels with string prefix.
add_suffix(suffix[, axis])	Suffix labels with string suffix.
add_trixels([n_partitions, num_workers, ...])	Combination of make_trixels() and set_trixels()
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])	Return whether all elements are True, potentially over an axis.
any(*[, axis, bool_only, skipna])	Return whether any element is True, potentially over an axis.
apply(func[, axis, raw, result_type, args])	Two-dimensional, size-mutable, potentially heterogeneous tabular data.
applymap(func[, na_action])	Apply a function to a Dataframe elementwise.
asfreq(freq[, method, how, normalize, ...])	Convert time series to specified frequency.
asof(where[, subset])	Return the last row(s) without any NaNs before where.
assign(**kwargs)	Assign new columns to a DataFrame.
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).
backfill(*[, axis, inplace, limit, downcast])	Synonym for DataFrame.fillna() with method='bfill'.
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.
boxplot([column, by, ax, fontsize, rot, ...])	Make a box plot from DataFrame columns.
buffer(distance[, resolution])	Returns a GeoSeries of geometries representing all points within a given distance of each geometric object.
clear_to_level([inplace])	Clears location bits to level
clip(mask[, keep_geom_type])	Clip points, lines, or polygon geometries to the mask extent.
clip_by_rect(xmin, ymin, xmax, ymax)	Returns a GeoSeries of the portions of geometry within the given rectangle.
combine(other, func[, fill_value, overwrite])	Perform column-wise combine with another DataFrame.
combine_first(other)	Update null elements with value in the same location in other.
compare(other[, align_axis, keep_shape, ...])	Compare to another DataFrame 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(*args, **kwargs)	Convert columns to best possible dtypes using dtypes supporting pd.NA.
copy([deep])	Two-dimensional, size-mutable, potentially heterogeneous tabular data.
corr([method, min_periods, numeric_only])	Compute pairwise correlation of columns, excluding NA/null values.
corrwith(other[, axis, drop, method, ...])	Compute pairwise correlation.
count([axis, numeric_only])	Count non-NA cells for each column or row.
cov([min_periods, ddof, numeric_only])	Compute pairwise covariance of columns, excluding NA/null 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, axis])	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.
dissolve([by, aggfunc, as_index, level, ...])	Dissolve geometries within groupby into single observation.
distance(other[, align])	Returns a Series containing the distance to aligned other.
div(other[, axis, level, fill_value])	Get Floating division of dataframe and other, element-wise (binary operator truediv).
divide(other[, axis, level, fill_value])	Get Floating division of dataframe and other, element-wise (binary operator truediv).
dot(other)	Compute the matrix multiplication between the DataFrame and other.
drop([labels, axis, index, columns, level, ...])	Drop specified labels from rows or columns.
drop_duplicates([subset, keep, inplace, ...])	Return DataFrame with duplicate rows removed.
drop_na_sids([inplace])	Drop all rows that have NA values for the SIDs and cast the column to numpy.int64
droplevel(level[, axis])	Return Series/DataFrame with requested index / column level(s) removed.
dropna(*[, axis, how, thresh, subset, ...])	Remove missing values.
duplicated([subset, keep])	Return boolean Series denoting duplicate rows.
eq(other[, axis, level])	Get Equal to of dataframe 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.
eval(expr, *[, inplace])	Evaluate a string describing operations on DataFrame columns.
ewm([com, span, halflife, alpha, ...])	Provide exponentially weighted (EW) calculations.
expanding([min_periods, axis, method])	Provide expanding window calculations.
explode([column, 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
ffill(*[, axis, inplace, limit, downcast])	Synonym for DataFrame.fillna() with method='ffill'.
fillna([value, method, axis, inplace, ...])	Fill NA/NaN values using the specified method.
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 non-NA value is found.
floordiv(other[, axis, level, fill_value])	Get Integer division of dataframe and other, element-wise (binary operator floordiv).
from_dict(data[, geometry, crs])	Construct GeoDataFrame from dict of array-like or dicts by overriding DataFrame.from_dict method with geometry and crs
from_features(features[, crs, columns])	Alternate constructor to create GeoDataFrame from an iterable of features or a feature collection.
from_file(filename, **kwargs)	Alternate constructor to create a GeoDataFrame from a file.
from_postgis(sql, con[, geom_col, crs, ...])	Alternate constructor to create a GeoDataFrame from a sql query containing a geometry column in WKB representation.
from_records(data[, index, exclude, ...])	Convert structured or record ndarray to DataFrame.
ge(other[, axis, level])	Get Greater than or equal to of dataframe 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).
get_coordinates([include_z, ignore_index, ...])	Gets coordinates from a GeoSeries as a DataFrame of floats.
groupby([by, axis, level, as_index, sort, ...])	Group DataFrame using a mapper or by a Series of columns.
gt(other[, axis, level])	Get Greater than of dataframe and other, element-wise (binary operator gt).
has_sids()
has_trixels()
head([n])	Return the first n rows.
hex()	Returns the hex16 representation of the stare column
hilbert_distance([total_bounds, level])	Calculate the distance along a Hilbert curve.
hist([column, by, grid, xlabelsize, xrot, ...])	Make a histogram of the DataFrame's columns.
idxmax([axis, skipna, numeric_only])	Return index of first occurrence of maximum over requested axis.
idxmin([axis, skipna, numeric_only])	Return index of first occurrence of minimum over requested axis.
infer_objects([copy])	Attempt to infer better dtypes for object columns.
info([verbose, buf, max_cols, memory_usage, ...])	Print a concise summary of a DataFrame.
insert(loc, column, value[, allow_duplicates])	Insert column into DataFrame at specified location.
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.
isetitem(loc, value)	Set the given value in the column with position loc.
isin(values)	Whether each element in the DataFrame is contained in values.
isna()	Detect missing values.
isnull()	DataFrame.isnull is an alias for DataFrame.isna.
items()	Iterate over (column name, Series) pairs.
iterfeatures([na, show_bbox, drop_id])	Returns an iterator that yields feature dictionaries that comply with __geo_interface__
iterrows()	Iterate over DataFrame rows as (index, Series) pairs.
itertuples([index, name])	Iterate over DataFrame rows as namedtuples.
join(other[, on, how, lsuffix, rsuffix, ...])	Join columns of another DataFrame.
keys()	Get the 'info axis' (see Indexing for more).
kurt([axis, skipna, numeric_only])	Return unbiased kurtosis over requested axis.
kurtosis([axis, skipna, 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 non-NA value is found.
le(other[, axis, level])	Get Less than or equal to of dataframe and other, element-wise (binary operator le).
lt(other[, axis, level])	Get Less than of dataframe and other, element-wise (binary operator lt).
make_sids(level[, convex, force_ccw, ...])	Generates and returns the STARE representation of each feauture.
make_tids([column, end_column, forward_res, ...])	Generates and returns the STARE representation of each feauture.
make_trixels([sid_column, n_partitions, ...])	Returns a Polygon or Multipolygon GeoSeries containing the trixels referred by the STARE indices
make_valid()	Repairs invalid geometries.
mask(cond[, other, inplace, axis, level])	Replace values where the condition is True.
max([axis, skipna, numeric_only])	Return the maximum of the values over the requested axis.
mean([axis, skipna, numeric_only])	Return the mean of the values over the requested axis.
median([axis, skipna, numeric_only])	Return the median of the values over the requested axis.
melt([id_vars, value_vars, var_name, ...])	Unpivot a DataFrame from wide to long format, optionally leaving identifiers set.
memory_usage([index, deep])	Return the memory usage of each column in bytes.
merge(*args, **kwargs)	Merge two GeoDataFrame objects with a database-style join.
min([axis, skipna, numeric_only])	Return the minimum of the values over the requested axis.
minimum_bounding_circle()	Returns a GeoSeries of geometries representing the minimum bounding circle that encloses each geometry.
minimum_bounding_radius()	Returns a Series of the radii of the minimum bounding circles that enclose each geometry.
mod(other[, axis, level, fill_value])	Get Modulo of dataframe and other, element-wise (binary operator mod).
mode([axis, numeric_only, dropna])	Get the mode(s) of each element along the selected axis.
mul(other[, axis, level, fill_value])	Get Multiplication of dataframe and other, element-wise (binary operator mul).
multiply(other[, axis, level, fill_value])	Get Multiplication of dataframe and other, element-wise (binary operator mul).
ne(other[, axis, level])	Get Not equal to of dataframe and other, element-wise (binary operator ne).
nlargest(n, columns[, keep])	Return the first n rows ordered by columns in descending order.
normalize()	Returns a GeoSeries of normalized geometries to normal form (or canonical form).
notna()	Detect existing (non-missing) values.
notnull()	DataFrame.notnull is an alias for DataFrame.notna.
nsmallest(n, columns[, keep])	Return the first n rows ordered by columns in ascending order.
nunique([axis, dropna])	Count number of distinct elements in specified axis.
overlaps(other[, align])	Returns True for all aligned geometries that overlap other, else False.
overlay(right[, how, keep_geom_type, make_valid])	Perform spatial overlay between GeoDataFrames.
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 chainable functions that expect Series or DataFrames.
pivot(*, columns[, index, values])	Return reshaped DataFrame organized by given index / column values.
pivot_table([values, index, columns, ...])	Create a spreadsheet-style pivot table as a DataFrame.
plot([trixels, boundary])	Generate a plot with matplotlib.
pop(item)	Return item and drop from frame.
pow(other[, axis, level, fill_value])	Get Exponential power of dataframe and other, element-wise (binary operator pow).
prod([axis, skipna, numeric_only, min_count])	Return the product of the values over the requested axis.
product([axis, skipna, numeric_only, min_count])	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, axis, numeric_only, ...])	Return values at the given quantile over requested axis.
query(expr, *[, inplace])	Query the columns of a DataFrame with a boolean expression.
radd(other[, axis, level, fill_value])	Get Addition of dataframe and other, element-wise (binary operator radd).
rank([axis, method, numeric_only, ...])	Compute numerical data ranks (1 through n) along axis.
rdiv(other[, axis, level, fill_value])	Get Floating division of dataframe and other, element-wise (binary operator rtruediv).
reindex([labels, index, columns, axis, ...])	Conform DataFrame 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([mapper, index, columns, axis, copy, ...])	Rename columns or index labels.
rename_axis([mapper, index, columns, axis, ...])	Set the name of the axis for the index or columns.
rename_geometry(col[, inplace])	Renames the GeoDataFrame geometry column to the specified name.
reorder_levels(order[, axis])	Rearrange index levels using input order.
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, inplace, ...])	Reset the index, or a level of it.
rfloordiv(other[, axis, level, fill_value])	Get Integer division of dataframe and other, element-wise (binary operator rfloordiv).
rmod(other[, axis, level, fill_value])	Get Modulo of dataframe and other, element-wise (binary operator rmod).
rmul(other[, axis, level, fill_value])	Get Multiplication of dataframe 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 a DataFrame to a variable number of decimal places.
rpow(other[, axis, level, fill_value])	Get Exponential power of dataframe and other, element-wise (binary operator rpow).
rsub(other[, axis, level, fill_value])	Get Subtraction of dataframe and other, element-wise (binary operator rsub).
rtruediv(other[, axis, level, fill_value])	Get Floating division of dataframe and other, element-wise (binary operator rtruediv).
sample([n, frac, replace, weights, ...])	Return a random sample of items from an axis of object.
sample_points(size[, method, seed])	Sample points from each geometry.
scale([xfact, yfact, zfact, origin])	Returns a GeoSeries with scaled geometries.
select_dtypes([include, exclude])	Return a subset of the DataFrame's columns based on the column dtypes.
sem([axis, skipna, ddof, numeric_only])	Return unbiased standard error of the mean over requested axis.
set_axis(labels, *[, axis, copy])	Assign desired index to given axis.
set_crs([crs, epsg, inplace, allow_override])	Set the Coordinate Reference System (CRS) of the GeoDataFrame.
set_flags(*[, copy, allows_duplicate_labels])	Return a new object with updated flags.
set_geometry(col[, drop, inplace, crs])	Set the GeoDataFrame geometry using either an existing column or the specified input.
set_index(keys, *[, drop, append, inplace, ...])	Set the DataFrame index using existing columns.
set_sids(col[, inplace])	Set the StareDataFrame spatial indices using either an existing column or the specified input.
set_tids(col[, inplace])	Set the StareDataFrame temporal indices using either an existing column or the specified input.
set_trixels(col[, inplace])	Set the trixel column
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.
sjoin(df, *args, **kwargs)	Spatial join of two GeoDataFrames.
sjoin_nearest(right[, how, max_distance, ...])	Spatial join of two GeoDataFrames based on the distance between their geometries.
skew([xs, ys, origin, use_radians])	Returns a GeoSeries with skewed geometries.
sort_index(*[, axis, level, ascending, ...])	Sort object by labels (along an axis).
sort_values(by, *[, axis, ascending, ...])	Sort by the values along either axis.
spatial_level()	Returns the spatial level of each feature
split_antimeridian([inplace, drop])	Splits trixels at the antimeridian
squeeze([axis])	Squeeze 1 dimensional axis objects into scalars.
stack([level, dropna])	Stack the prescribed level(s) from columns to index.
stare_disjoint(other[, method, n_workers])	Returns a Series of dtype('bool') with value True for each geometry that is disjoint from other.
stare_dissolve([by, num_workers, geom, aggfunc])	Dissolves a dataframe subject to a field.
stare_intersection(other)	Returns a STARESeries of the (STARE) spatial intersection of self with other.
stare_intersects(other[, method, ...])	Returns a Series of dtype('bool') with value True for each geometry that intersects other.
std([axis, skipna, ddof, numeric_only])	Return sample standard deviation over requested axis.
sub(other[, axis, level, fill_value])	Get Subtraction of dataframe and other, element-wise (binary operator sub).
subtract(other[, axis, level, fill_value])	Get Subtraction of dataframe and other, element-wise (binary operator sub).
sum([axis, skipna, numeric_only, min_count])	Return the sum of the values over the requested axis.
swapaxes(axis1, axis2[, copy])	Interchange axes and swap values axes appropriately.
swaplevel([i, j, axis])	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(indices[, axis])	Return the elements in the given positional indices along an axis.
to_array(column[, shape, pivot])	Converts the 'column' to a numpy array.
to_arrays([shape, pivot])	Converts a STAREDataFrame into a dictionary of arrays; one array per column/field.
to_clipboard([excel, sep])	Copy object to the system clipboard.
to_crs([crs, epsg, inplace])	Transform geometries 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([orient, into, index])	Convert the DataFrame to a dictionary.
to_excel(excel_writer[, sheet_name, na_rep, ...])	Write object to an Excel sheet.
to_feather(path[, index, compression, ...])	Write a GeoDataFrame to the Feather format.
to_file(filename[, driver, schema, index])	Write the GeoDataFrame to a file.
to_gbq(destination_table[, project_id, ...])	Write a DataFrame to a Google BigQuery table.
to_hdf(path_or_buf, key[, mode, complevel, ...])	Write the contained data to an HDF5 file using HDFStore.
to_html([buf, columns, col_space, header, ...])	Render a DataFrame as an HTML table.
to_json([na, show_bbox, drop_id, to_wgs84])	Returns a GeoJSON representation of the GeoDataFrame as a string.
to_latex([buf, columns, header, index, ...])	Render object to a LaTeX tabular, longtable, or nested table.
to_markdown([buf, mode, index, storage_options])	Print DataFrame in Markdown-friendly format.
to_numpy([dtype, copy, na_value])	Convert the DataFrame to a NumPy array.
to_orc([path, engine, index, engine_kwargs])	Write a DataFrame to the ORC format.
to_parquet(path[, index, compression, ...])	Write a GeoDataFrame to the Parquet format.
to_period([freq, axis, copy])	Convert DataFrame from DatetimeIndex to PeriodIndex.
to_pickle(path[, compression, protocol, ...])	Pickle (serialize) object to file.
to_postgis(name, con[, schema, if_exists, ...])	Upload GeoDataFrame into PostGIS database.
to_records([index, column_dtypes, index_dtypes])	Convert DataFrame to a NumPy record array.
to_scidb(connection)
to_sidecar(file_name[, cover, shuffle, zlib])	Writes STARE Sidecar
to_sids_array([shape, pivot])
to_sql(name, con[, schema, if_exists, ...])	Write records stored in a DataFrame to a SQL database.
to_stare_level(level[, inplace, clear_to_level])	Changes level of STARE index values to level; optionally clears location bits up to level.
to_stare_singlelevel([level, inplace])	Changes the STARE index values to single level representation (in contrary to multiresolution).
to_stata(path, *[, convert_dates, ...])	Export DataFrame object to Stata dta format.
to_string([buf, columns, col_space, header, ...])	Render a DataFrame to a console-friendly tabular output.
to_timestamp([freq, how, axis, copy])	Cast to DatetimeIndex of timestamps, at beginning of period.
to_wkb([hex])	Encode all geometry columns in the GeoDataFrame to WKB.
to_wkt(**kwargs)	Encode all geometry columns in the GeoDataFrame to WKT.
to_xarray()	Return an xarray object from the pandas object.
to_xml([path_or_buffer, index, root_name, ...])	Render a DataFrame to an XML document.
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 DataFrame with the same axis shape as self.
translate([xoff, yoff, zoff])	Returns a GeoSeries with translated geometries.
transpose(*args[, copy])	Transpose index and columns.
trixel_area([r])	Returns the approximate area of the trixel
trixel_centerpoints([vertices])	Returns the trixel centers as shapely points.
trixel_centers([vertices])	Returns the trixel centers.
trixel_centers_ecef([vertices])	Returns the trixel centers as ECEF vectors.
trixel_corners([vertices, from_trixels])	Returns corners of trixels as lon/lat.
trixel_corners_ecef([vertices])	Returns ECEF norm vectors of great circles constraining the trixels.
trixel_grings([vertices])	Returns corners of trixels as ECEF.
trixel_vertices()	Returns the vertices and centerpoints of the trixels.
truediv(other[, axis, level, fill_value])	Get Floating division of dataframe and other, element-wise (binary operator truediv).
truncate([before, after, axis, copy])	Truncate a Series or DataFrame before and after some index value.
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.
unstack([level, fill_value])	Pivot a level of the (necessarily hierarchical) index labels.
update(other[, join, overwrite, ...])	Modify in place using non-NA values from another DataFrame.
value_counts([subset, normalize, sort, ...])	Return a Series containing counts of unique rows in the DataFrame.
var([axis, skipna, ddof, numeric_only])	Return unbiased variance over requested axis.
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.
write_pods(pod_root, level, chunk_name[, ...])	Writes dataframe into a STAREPods hierarchy.
write_pods_granule(pod_root, level, chunk_name)
write_pods_spatial(pod_root, level, chunk_name)
write_pods_tpod(pod_root, level, chunk_name)	Parameters:
xs(key[, axis, level, drop_level])	Return cross-section from the Series/DataFrame.

Attributes

T	The transpose of the DataFrame.
area	Returns a Series containing the area of each geometry in the GeoSeries expressed in the units of the CRS.
at	Access a single value for a row/column label pair.
attrs	Dictionary of global attributes of this dataset.
axes	Return a list representing the axes of the DataFrame.
boundary	Returns a GeoSeries of lower dimensional objects representing each geometry'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.
columns	The column labels of the DataFrame.
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.
dtypes	Return the dtypes in the DataFrame.
empty	Indicator whether Series/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	Geometry data for GeoDataFrame
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.
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 (row labels) of the DataFrame.
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_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_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.
ndim	Return an int representing the number of axes / array dimensions.
shape	Return a tuple representing the dimensionality of the DataFrame.
sindex	Generate the spatial index
size	Return an int representing the number of elements in this object.
style	Returns a Styler object.
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 a Numpy representation of the DataFrame.