Series#

The following table lists both implemented and not implemented methods. If you have need of an operation that is listed as not implemented, feel free to open an issue on the GitHub repository, or give a thumbs up to already created issues. Contributions are also welcome!

The following table is structured as follows: The first column contains the method name. The second column contains link to a description of corresponding pandas method. The third column is a flag for whether or not there is an implementation in Xorbits for the method in the left column. Y stands for yes, N stands for no, P standsfor partial (meaning some parameters may not be supported yet), and D stands for default to pandas.

Constructor#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series`	Series	Y

Attributes#

Axes

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.index`	Series.index	Y
`Series.array`	Series.array	Y
`Series.values`	Series.values	Y
`Series.dtype`	Series.dtype	Y
`Series.shape`	Series.shape	Y
`Series.nbytes`	Series.nbytes	Y
`Series.ndim`	Series.ndim	Y
`Series.size`	Series.size	Y
`Series.T`	Series.T	Y
`Series.memory_usage`	Series.memory_usage	Y
`Series.hasnans`	Series.hasnans	Y
`Series.empty`	Series.empty	Y
`Series.dtypes`	Series.dtypes	Y
`Series.name`	Series.name	Y
`Series.flags`	Series.flags	Y
`Series.set_flags`	Series.set_flags	Y

Conversion#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.astype`	Series.astype	Y
`Series.convert_dtypes`	Series.convert_dtypes	Y
`Series.infer_objects`	Series.infer_objects	Y
`Series.copy`	Series.copy	Y
`Series.bool`	Series.bool	Y
`Series.to_numpy`	Series.to_numpy	Y
`Series.to_period`	Series.to_period	Y
`Series.to_timestamp`	Series.to_timestamp	Y
`Series.to_list`	Series.to_list	Y
`Series.__array__`	Series.__array__	Y

Indexing, iteration#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.get`	Series.get	Y
`Series.at`	Series.at	Y
`Series.iat`	Series.iat	Y
`Series.loc`	Series.loc	Y
`Series.iloc`	Series.iloc	Y
`Series.__iter__`	Series.__iter__	Y
`Series.items`	Series.items	Y
`Series.iteritems`	Series.iteritems	Y
`Series.keys`	Series.keys	Y
`Series.pop`	Series.pop	Y
`Series.item`	Series.item	Y
`Series.xs`	Series.xs	Y

For more information on .at, .iat, .loc, and .iloc, see the indexing documentation.

Binary operator functions#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.add`	Series.add	Y
`Series.sub`	Series.sub	Y
`Series.mul`	Series.mul	Y
`Series.div`	Series.div	Y
`Series.truediv`	Series.truediv	Y
`Series.floordiv`	Series.floordiv	Y
`Series.mod`	Series.mod	Y
`Series.pow`	Series.pow	Y
`Series.radd`	Series.radd	Y
`Series.rsub`	Series.rsub	Y
`Series.rmul`	Series.rmul	Y
`Series.rdiv`	Series.rdiv	Y
`Series.rtruediv`	Series.rtruediv	Y
`Series.rfloordiv`	Series.rfloordiv	Y
`Series.rmod`	Series.rmod	Y
`Series.rpow`	Series.rpow	Y
`Series.combine`	Series.combine	Y
`Series.combine_first`	Series.combine_first	Y
`Series.round`	Series.round	Y
`Series.lt`	Series.lt	Y
`Series.gt`	Series.gt	Y
`Series.le`	Series.le	Y
`Series.ge`	Series.ge	Y
`Series.ne`	Series.ne	Y
`Series.eq`	Series.eq	Y
`Series.product`	Series.product	Y
`Series.dot`	Series.dot	Y

Function application, GroupBy & window#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.apply`	Series.apply	Y
`Series.agg`	Series.agg	Y
`Series.aggregate`	Series.aggregate	Y
`Series.transform`	Series.transform	Y
`Series.map`	Series.map	Y
`Series.groupby`	Series.groupby	Y
`Series.rolling`	Series.rolling	Y
`Series.expanding`	Series.expanding	Y
`Series.ewm`	Series.ewm	Y
`Series.pipe`	Series.pipe	Y

Computations / descriptive stats#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.abs`	Series.abs	Y
`Series.all`	Series.all	Y
`Series.any`	Series.any	Y
`Series.autocorr`	Series.autocorr	Y
`Series.between`	Series.between	Y
`Series.clip`	Series.clip	Y
`Series.corr`	Series.corr	Y
`Series.count`	Series.count	Y
`Series.cov`	Series.cov	Y
`Series.cummax`	Series.cummax	Y
`Series.cummin`	Series.cummin	Y
`Series.cumprod`	Series.cumprod	Y
`Series.cumsum`	Series.cumsum	Y
`Series.describe`	Series.describe	Y
`Series.diff`	Series.diff	Y
`Series.factorize`	Series.factorize	Y
`Series.kurt`	Series.kurt	Y
`Series.mad`	Series.mad	Y
`Series.max`	Series.max	Y
`Series.mean`	Series.mean	Y
`Series.median`	Series.median	Y
`Series.min`	Series.min	Y
`Series.mode`	Series.mode	Y
`Series.nlargest`	Series.nlargest	Y
`Series.nsmallest`	Series.nsmallest	Y
`Series.pct_change`	Series.pct_change	Y
`Series.prod`	Series.prod	Y
`Series.quantile`	Series.quantile	Y
`Series.rank`	Series.rank	Y
`Series.sem`	Series.sem	Y
`Series.skew`	Series.skew	Y
`Series.std`	Series.std	Y
`Series.sum`	Series.sum	Y
`Series.var`	Series.var	Y
`Series.kurtosis`	Series.kurtosis	Y
`Series.unique`	Series.unique	Y
`Series.nunique`	Series.nunique	Y
`Series.is_unique`	Series.is_unique	Y
`Series.is_monotonic`	Series.is_monotonic	Y
`Series.is_monotonic_increasing`	Series.is_monotonic_increasing	Y
`Series.is_monotonic_decreasing`	Series.is_monotonic_decreasing	Y
`Series.value_counts`	Series.value_counts	Y

Reindexing / selection / label manipulation#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.align`	Series.align	Y
`Series.drop`	Series.drop	Y
`Series.droplevel`	Series.droplevel	Y
`Series.drop_duplicates`	Series.drop_duplicates	Y
`Series.duplicated`	Series.duplicated	Y
`Series.equals`	Series.equals	Y
`Series.first`	Series.first	Y
`Series.head`	Series.head	Y
`Series.idxmax`	Series.idxmax	Y
`Series.idxmin`	Series.idxmin	Y
`Series.isin`	Series.isin	Y
`Series.last`	Series.last	Y
`Series.reindex`	Series.reindex	Y
`Series.reindex_like`	Series.reindex_like	Y
`Series.rename`	Series.rename	Y
`Series.rename_axis`	Series.rename_axis	Y
`Series.reset_index`	Series.reset_index	Y
`Series.sample`	Series.sample	Y
`Series.set_axis`	Series.set_axis	Y
`Series.take`	Series.take	Y
`Series.tail`	Series.tail	Y
`Series.truncate`	Series.truncate	Y
`Series.where`	Series.where	Y
`Series.mask`	Series.mask	Y
`Series.add_prefix`	Series.add_prefix	Y
`Series.add_suffix`	Series.add_suffix	Y
`Series.filter`	Series.filter	Y

Missing data handling#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.backfill`	Series.backfill	Y
`Series.bfill`	Series.bfill	Y
`Series.dropna`	Series.dropna	Y
`Series.ffill`	Series.ffill	Y
`Series.fillna`	Series.fillna	Y
`Series.interpolate`	Series.interpolate	Y
`Series.isna`	Series.isna	Y
`Series.isnull`	Series.isnull	Y
`Series.notna`	Series.notna	Y
`Series.notnull`	Series.notnull	Y
`Series.pad`	Series.pad	Y
`Series.replace`	Series.replace	Y

Reshaping, sorting#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.argsort`	Series.argsort	Y
`Series.argmin`	Series.argmin	Y
`Series.argmax`	Series.argmax	Y
`Series.reorder_levels`	Series.reorder_levels	Y
`Series.sort_values`	Series.sort_values	Y
`Series.sort_index`	Series.sort_index	Y
`Series.swaplevel`	Series.swaplevel	Y
`Series.unstack`	Series.unstack	Y
`Series.explode`	Series.explode	Y
`Series.searchsorted`	Series.searchsorted	Y
`Series.ravel`	Series.ravel	Y
`Series.repeat`	Series.repeat	Y
`Series.squeeze`	Series.squeeze	Y
`Series.view`	Series.view	Y

Combining / comparing / joining / merging#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.append`	Series.append	Y
`Series.compare`	Series.compare	Y
`Series.update`	Series.update	Y

Accessors#

pandas provides dtype-specific methods under various accessors. These are separate namespaces within Series that only apply to specific data types.

Data Type	Accessor
Datetime, Timedelta, Period	dt
String	str
Categorical	cat
Sparse	sparse

Datetimelike properties#

Series.dt can be used to access the values of the series as datetimelike and return several properties. These can be accessed like Series.dt.<property>.

Datetime properties#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.dt.date`	Series.dt.date	Y
`Series.dt.time`	Series.dt.time	Y
`Series.dt.timetz`	Series.dt.timetz	Y
`Series.dt.year`	Series.dt.year	Y
`Series.dt.month`	Series.dt.month	Y
`Series.dt.day`	Series.dt.day	Y
`Series.dt.hour`	Series.dt.hour	Y
`Series.dt.minute`	Series.dt.minute	Y
`Series.dt.second`	Series.dt.second	Y
`Series.dt.microsecond`	Series.dt.microsecond	Y
`Series.dt.nanosecond`	Series.dt.nanosecond	Y
`Series.dt.week`	Series.dt.week	Y
`Series.dt.weekofyear`	Series.dt.weekofyear	Y
`Series.dt.dayofweek`	Series.dt.dayofweek	Y
`Series.dt.day_of_week`	Series.dt.day_of_week	Y
`Series.dt.weekday`	Series.dt.weekday	Y
`Series.dt.dayofyear`	Series.dt.dayofyear	Y
`Series.dt.day_of_year`	Series.dt.day_of_year	Y
`Series.dt.quarter`	Series.dt.quarter	Y
`Series.dt.is_month_start`	Series.dt.is_month_start	Y
`Series.dt.is_month_end`	Series.dt.is_month_end	Y
`Series.dt.is_quarter_start`	Series.dt.is_quarter_start	Y
`Series.dt.is_quarter_end`	Series.dt.is_quarter_end	Y
`Series.dt.is_year_start`	Series.dt.is_year_start	Y
`Series.dt.is_year_end`	Series.dt.is_year_end	Y
`Series.dt.is_leap_year`	Series.dt.is_leap_year	Y
`Series.dt.daysinmonth`	Series.dt.daysinmonth	Y
`Series.dt.days_in_month`	Series.dt.days_in_month	Y
`Series.dt.tz`	Series.dt.tz	Y
`Series.dt.freq`	Series.dt.freq	Y

Datetime methods#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.dt.isocalendar`	Series.dt.isocalendar	Y
`Series.dt.to_period`	Series.dt.to_period	Y
`Series.dt.to_pydatetime`	Series.dt.to_pydatetime	Y
`Series.dt.tz_localize`	Series.dt.tz_localize	Y
`Series.dt.tz_convert`	Series.dt.tz_convert	Y
`Series.dt.normalize`	Series.dt.normalize	Y
`Series.dt.strftime`	Series.dt.strftime	Y
`Series.dt.round`	Series.dt.round	Y
`Series.dt.floor`	Series.dt.floor	Y
`Series.dt.ceil`	Series.dt.ceil	Y
`Series.dt.month_name`	Series.dt.month_name	Y
`Series.dt.day_name`	Series.dt.day_name	Y

Period properties#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.dt.qyear`	Series.dt.qyear	Y
`Series.dt.start_time`	Series.dt.start_time	Y
`Series.dt.end_time`	Series.dt.end_time	Y

Timedelta properties#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.dt.days`	Series.dt.days	Y
`Series.dt.seconds`	Series.dt.seconds	Y
`Series.dt.microseconds`	Series.dt.microseconds	Y
`Series.dt.nanoseconds`	Series.dt.nanoseconds	Y
`Series.dt.components`	Series.dt.components	Y

Timedelta methods#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.dt.to_pytimedelta`	Series.dt.to_pytimedelta	Y
`Series.dt.total_seconds`	Series.dt.total_seconds	Y

String handling#

Series.str can be used to access the values of the series as strings and apply several methods to it. These can be accessed like Series.str.<function/property>.

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.str.capitalize`	Series.str.capitalize	Y
`Series.str.casefold`	Series.str.casefold	Y
`Series.str.cat`	Series.str.cat	Y
`Series.str.center`	Series.str.center	Y
`Series.str.contains`	Series.str.contains	Y
`Series.str.count`	Series.str.count	Y
`Series.str.decode`	Series.str.decode	Y
`Series.str.encode`	Series.str.encode	Y
`Series.str.endswith`	Series.str.endswith	Y
`Series.str.extract`	Series.str.extract	Y
`Series.str.extractall`	Series.str.extractall	Y
`Series.str.find`	Series.str.find	Y
`Series.str.findall`	Series.str.findall	Y
`Series.str.fullmatch`	Series.str.fullmatch	Y
`Series.str.get`	Series.str.get	Y
`Series.str.index`	Series.str.index	Y
`Series.str.join`	Series.str.join	Y
`Series.str.len`	Series.str.len	Y
`Series.str.ljust`	Series.str.ljust	Y
`Series.str.lower`	Series.str.lower	Y
`Series.str.lstrip`	Series.str.lstrip	Y
`Series.str.match`	Series.str.match	Y
`Series.str.normalize`	Series.str.normalize	Y
`Series.str.pad`	Series.str.pad	Y
`Series.str.partition`	Series.str.partition	Y
`Series.str.removeprefix`	Series.str.removeprefix	Y
`Series.str.removesuffix`	Series.str.removesuffix	Y
`Series.str.repeat`	Series.str.repeat	Y
`Series.str.replace`	Series.str.replace	Y
`Series.str.rfind`	Series.str.rfind	Y
`Series.str.rindex`	Series.str.rindex	Y
`Series.str.rjust`	Series.str.rjust	Y
`Series.str.rpartition`	Series.str.rpartition	Y
`Series.str.rstrip`	Series.str.rstrip	Y
`Series.str.slice`	Series.str.slice	Y
`Series.str.slice_replace`	Series.str.slice_replace	Y
`Series.str.split`	Series.str.split	Y
`Series.str.rsplit`	Series.str.rsplit	Y
`Series.str.startswith`	Series.str.startswith	Y
`Series.str.strip`	Series.str.strip	Y
`Series.str.swapcase`	Series.str.swapcase	Y
`Series.str.title`	Series.str.title	Y
`Series.str.translate`	Series.str.translate	Y
`Series.str.upper`	Series.str.upper	Y
`Series.str.wrap`	Series.str.wrap	Y
`Series.str.zfill`	Series.str.zfill	Y
`Series.str.isalnum`	Series.str.isalnum	Y
`Series.str.isalpha`	Series.str.isalpha	Y
`Series.str.isdigit`	Series.str.isdigit	Y
`Series.str.isspace`	Series.str.isspace	Y
`Series.str.islower`	Series.str.islower	Y
`Series.str.isupper`	Series.str.isupper	Y
`Series.str.istitle`	Series.str.istitle	Y
`Series.str.isnumeric`	Series.str.isnumeric	Y
`Series.str.isdecimal`	Series.str.isdecimal	Y
`Series.str.get_dummies`	Series.str.get_dummies	Y
`Series.str`	Series.str	Y
`Series.cat`	Series.cat	Y
`Series.dt`	Series.dt	Y
`Series.sparse`	Series.sparse	Y
`DataFrame.sparse`	DataFrame.sparse	Y
`Index.str`	Index.str	Y

Categorical accessor#

Categorical-dtype specific methods and attributes are available under the Series.cat accessor.

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.cat.categories`	Series.cat.categories	Y
`Series.cat.ordered`	Series.cat.ordered	Y
`Series.cat.codes`	Series.cat.codes	Y
`Series.cat.rename_categories`	Series.cat.rename_categories	Y
`Series.cat.reorder_categories`	Series.cat.reorder_categories	Y
`Series.cat.add_categories`	Series.cat.add_categories	Y
`Series.cat.remove_categories`	Series.cat.remove_categories	Y
`Series.cat.remove_unused_categories`	Series.cat.remove_unused_categories	Y
`Series.cat.set_categories`	Series.cat.set_categories	Y
`Series.cat.as_ordered`	Series.cat.as_ordered	Y
`Series.cat.as_unordered`	Series.cat.as_unordered	Y

Sparse accessor#

Sparse-dtype specific methods and attributes are provided under the Series.sparse accessor.

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.sparse.npoints`	Series.sparse.npoints	Y
`Series.sparse.density`	Series.sparse.density	Y
`Series.sparse.fill_value`	Series.sparse.fill_value	Y
`Series.sparse.sp_values`	Series.sparse.sp_values	Y
`Series.sparse.from_coo`	Series.sparse.from_coo	Y
`Series.sparse.to_coo`	Series.sparse.to_coo	Y

Flags#

Flags refer to attributes of the xorbits.pandas object. Properties of the dataset (like the date is was recorded, the URL it was accessed from, etc.) should be stored in Series.attrs.

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Flags`	Flags	Y

Metadata#

Series.attrs is a dictionary for storing global metadata for this Series.

Warning

Series.attrs is considered experimental and may change without warning.

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.attrs`	Series.attrs	Y

Plotting#

Series.plot is both a callable method and a namespace attribute for specific plotting methods of the form Series.plot.<kind>.

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.plot`	Series.plot	Y
`Series.plot.area`	Series.plot.area	Y
`Series.plot.bar`	Series.plot.bar	Y
`Series.plot.barh`	Series.plot.barh	Y
`Series.plot.box`	Series.plot.box	Y
`Series.plot.density`	Series.plot.density	Y
`Series.plot.hist`	Series.plot.hist	Y
`Series.plot.kde`	Series.plot.kde	Y
`Series.plot.line`	Series.plot.line	Y
`Series.plot.pie`	Series.plot.pie	Y
`Series.hist`	Series.hist	Y

Serialization / IO / conversion#

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.to_pickle`	Series.to_pickle	Y
`Series.to_csv`	Series.to_csv	Y
`Series.to_dict`	Series.to_dict	Y
`Series.to_excel`	Series.to_excel	Y
`Series.to_frame`	Series.to_frame	Y
`Series.to_xarray`	Series.to_xarray	Y
`Series.to_hdf`	Series.to_hdf	Y
`Series.to_sql`	Series.to_sql	Y
`Series.to_json`	Series.to_json	Y
`Series.to_string`	Series.to_string	Y
`Series.to_clipboard`	Series.to_clipboard	Y
`Series.to_latex`	Series.to_latex	Y
`Series.to_markdown`	Series.to_markdown	Y

`xorbits.pandas`	`pandas`	Implemented? (Y/N/P/D)	Notes for Current implementation
`Series.asfreq`	Series.asfreq	Y
`Series.asof`	Series.asof	Y
`Series.shift`	Series.shift	Y
`Series.first_valid_index`	Series.first_valid_index	Y
`Series.last_valid_index`	Series.last_valid_index	Y
`Series.resample`	Series.resample	Y
`Series.tz_convert`	Series.tz_convert	Y
`Series.tz_localize`	Series.tz_localize	Y
`Series.at_time`	Series.at_time	Y
`Series.between_time`	Series.between_time	Y
`Series.tshift`	Series.tshift	Y
`Series.slice_shift`	Series.slice_shift	Y

Series#

Constructor#

Attributes#

Conversion#

Indexing, iteration#

Binary operator functions#

Function application, GroupBy & window#

Computations / descriptive stats#

Reindexing / selection / label manipulation#

Missing data handling#

Reshaping, sorting#

Combining / comparing / joining / merging#

Time Series-related#

Accessors#

Datetimelike properties#

Datetime properties#

Datetime methods#

Period properties#

Timedelta properties#

Timedelta methods#

String handling#

Categorical accessor#

Sparse accessor#

Flags#

Metadata#

Plotting#

Serialization / IO / conversion#

This Page