pandas
This page gives an overview of all public pandas objects, functions and methods. In general, all classes and functions exposed in the top-level pandas.* namespace are regarded as public.
Further some of the subpackages are public, including pandas.errors, pandas.plotting, and pandas.testing. Certain functions in the the pandas.io and pandas.tseries submodules are public as well (those mentioned in the documentation). Further, the pandas.api.types subpackage holds some public functions related to data types in pandas.
Warning
The pandas.core, pandas.compat, and pandas.util top-level modules are considered to be PRIVATE. Stability of functionality in those modules in not guaranteed.
read_pickle
read_table read_csv read_fwf read_msgpack
read_clipboard
read_excel ExcelFile.parse
read_json
pandas.io.json
json_normalize build_table_schema
pandas
read_html
read_hdf HDFStore.put HDFStore.append HDFStore.get HDFStore.select
read_feather
read_sas
read_sql_table read_sql_query read_sql
pandas.io.gbq
read_gbq
pandas
read_stata
pandas.io.stata
StataReader.data StataReader.data_label StataReader.value_labels StataReader.variable_labels StataWriter.write_file
pandas
melt pivot pivot_table crosstab cut qcut merge merge_ordered merge_asof concat get_dummies factorize unique wide_to_long
isnull notnull
to_numeric
to_datetime to_timedelta date_range bdate_range period_range timedelta_range infer_freq
eval
test
pandas
Series
- Axes
- index: axis labels
Series.values Series.dtype Series.ftype Series.shape Series.nbytes Series.ndim Series.size Series.strides Series.itemsize Series.base Series.T Series.memory_usage
Series.astype Series.copy Series.isnull Series.notnull
Series.get Series.at Series.iat Series.loc Series.iloc Series.__iter__ Series.iteritems
For more information on .at, .iat, .loc, and .iloc, see the indexing documentation <indexing>.
Series.add Series.sub Series.mul Series.div Series.truediv Series.floordiv Series.mod Series.pow Series.radd Series.rsub Series.rmul Series.rdiv Series.rtruediv Series.rfloordiv Series.rmod Series.rpow Series.combine Series.combine_first Series.round Series.lt Series.gt Series.le Series.ge Series.ne Series.eq
Series.apply Series.aggregate Series.transform Series.map Series.groupby Series.rolling Series.expanding Series.ewm
Series.abs Series.all Series.any Series.autocorr Series.between Series.clip Series.clip_lower Series.clip_upper Series.corr Series.count Series.cov Series.cummax Series.cummin Series.cumprod Series.cumsum Series.describe Series.diff Series.factorize Series.kurt Series.mad Series.max Series.mean Series.median Series.min Series.mode Series.nlargest Series.nsmallest Series.pct_change Series.prod Series.quantile Series.rank Series.sem Series.skew Series.std Series.sum Series.var Series.unique Series.nunique Series.is_unique Series.is_monotonic Series.is_monotonic_increasing Series.is_monotonic_decreasing Series.value_counts
Series.align Series.drop Series.drop_duplicates Series.duplicated Series.equals Series.first Series.head Series.idxmax Series.idxmin Series.isin Series.last Series.reindex Series.reindex_like Series.rename Series.rename_axis Series.reset_index Series.sample Series.select Series.take Series.tail Series.truncate Series.where Series.mask
Series.dropna Series.fillna Series.interpolate
Series.argsort Series.reorder_levels Series.sort_values Series.sort_index Series.swaplevel Series.unstack Series.searchsorted
Series.append Series.replace Series.update
Series.asfreq Series.asof Series.shift Series.first_valid_index Series.last_valid_index Series.resample Series.tz_convert Series.tz_localize
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
Series.dt.date Series.dt.time Series.dt.year Series.dt.month Series.dt.day Series.dt.hour Series.dt.minute Series.dt.second Series.dt.microsecond Series.dt.nanosecond Series.dt.week Series.dt.weekofyear Series.dt.dayofweek Series.dt.weekday Series.dt.weekday_name Series.dt.dayofyear Series.dt.quarter Series.dt.is_month_start Series.dt.is_month_end Series.dt.is_quarter_start Series.dt.is_quarter_end Series.dt.is_year_start Series.dt.is_year_end Series.dt.is_leap_year Series.dt.daysinmonth Series.dt.days_in_month Series.dt.tz Series.dt.freq
Datetime Methods
Series.dt.to_period Series.dt.to_pydatetime Series.dt.tz_localize Series.dt.tz_convert Series.dt.normalize Series.dt.strftime Series.dt.round Series.dt.floor Series.dt.ceil
Timedelta Properties
Series.dt.days Series.dt.seconds Series.dt.microseconds Series.dt.nanoseconds Series.dt.components
Timedelta Methods
Series.dt.to_pytimedelta Series.dt.total_seconds
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>.
Series.str.capitalize Series.str.cat Series.str.center Series.str.contains Series.str.count Series.str.decode Series.str.encode Series.str.endswith Series.str.extract Series.str.extractall Series.str.find Series.str.findall Series.str.get Series.str.index Series.str.join Series.str.len Series.str.ljust Series.str.lower Series.str.lstrip Series.str.match Series.str.normalize Series.str.pad Series.str.partition Series.str.repeat Series.str.replace Series.str.rfind Series.str.rindex Series.str.rjust Series.str.rpartition Series.str.rstrip Series.str.slice Series.str.slice_replace Series.str.split Series.str.rsplit Series.str.startswith Series.str.strip Series.str.swapcase Series.str.title Series.str.translate Series.str.upper Series.str.wrap Series.str.zfill Series.str.isalnum Series.str.isalpha Series.str.isdigit Series.str.isspace Series.str.islower Series.str.isupper Series.str.istitle Series.str.isnumeric Series.str.isdecimal Series.str.get_dummies
If the Series is of dtype category, Series.cat can be used to change the the categorical data. This accessor is similar to the Series.dt or Series.str and has the following usable methods and properties:
Series.cat.categories Series.cat.ordered Series.cat.codes
Series.cat.rename_categories Series.cat.reorder_categories Series.cat.add_categories Series.cat.remove_categories Series.cat.remove_unused_categories Series.cat.set_categories Series.cat.as_ordered Series.cat.as_unordered
To create a Series of dtype category, use cat = s.astype("category").
The following two Categorical constructors are considered API but should only be used when adding ordering information or special categories is need at creation time of the categorical data:
Categorical
Categorical.from_codes
np.asarray(categorical) works by implementing the array interface. Be aware, that this converts the Categorical back to a numpy array, so categories and order information is not preserved!
Categorical.__array__
Series.plot is both a callable method and a namespace attribute for specific plotting methods of the form Series.plot.<kind>.
Series.plot
Series.plot.area Series.plot.bar Series.plot.barh Series.plot.box Series.plot.density Series.plot.hist Series.plot.kde Series.plot.line Series.plot.pie
Series.hist
Series.from_csv Series.to_pickle Series.to_csv Series.to_dict Series.to_excel Series.to_frame Series.to_xarray Series.to_hdf Series.to_sql Series.to_msgpack Series.to_json Series.to_sparse Series.to_dense Series.to_string Series.to_clipboard
SparseSeries.to_coo SparseSeries.from_coo
DataFrame
Axes
- index: row labels
- columns: column labels
DataFrame.as_matrix DataFrame.dtypes DataFrame.ftypes DataFrame.get_dtype_counts DataFrame.get_ftype_counts DataFrame.select_dtypes DataFrame.values DataFrame.axes DataFrame.ndim DataFrame.size DataFrame.shape DataFrame.memory_usage
DataFrame.astype DataFrame.convert_objects DataFrame.copy DataFrame.isnull DataFrame.notnull
DataFrame.head DataFrame.at DataFrame.iat DataFrame.loc DataFrame.iloc DataFrame.insert DataFrame.__iter__ DataFrame.iteritems DataFrame.iterrows DataFrame.itertuples DataFrame.lookup DataFrame.pop DataFrame.tail DataFrame.xs DataFrame.isin DataFrame.where DataFrame.mask DataFrame.query
For more information on .at, .iat, .loc, and .iloc, see the indexing documentation <indexing>.
DataFrame.add DataFrame.sub DataFrame.mul DataFrame.div DataFrame.truediv DataFrame.floordiv DataFrame.mod DataFrame.pow DataFrame.radd DataFrame.rsub DataFrame.rmul DataFrame.rdiv DataFrame.rtruediv DataFrame.rfloordiv DataFrame.rmod DataFrame.rpow DataFrame.lt DataFrame.gt DataFrame.le DataFrame.ge DataFrame.ne DataFrame.eq DataFrame.combine DataFrame.combine_first
DataFrame.apply DataFrame.applymap DataFrame.aggregate DataFrame.transform DataFrame.groupby DataFrame.rolling DataFrame.expanding DataFrame.ewm
DataFrame.abs DataFrame.all DataFrame.any DataFrame.clip DataFrame.clip_lower DataFrame.clip_upper DataFrame.corr DataFrame.corrwith DataFrame.count DataFrame.cov DataFrame.cummax DataFrame.cummin DataFrame.cumprod DataFrame.cumsum DataFrame.describe DataFrame.diff DataFrame.eval DataFrame.kurt DataFrame.mad DataFrame.max DataFrame.mean DataFrame.median DataFrame.min DataFrame.mode DataFrame.pct_change DataFrame.prod DataFrame.quantile DataFrame.rank DataFrame.round DataFrame.sem DataFrame.skew DataFrame.sum DataFrame.std DataFrame.var
DataFrame.add_prefix DataFrame.add_suffix DataFrame.align DataFrame.drop DataFrame.drop_duplicates DataFrame.duplicated DataFrame.equals DataFrame.filter DataFrame.first DataFrame.head DataFrame.idxmax DataFrame.idxmin DataFrame.last DataFrame.reindex DataFrame.reindex_axis DataFrame.reindex_like DataFrame.rename DataFrame.rename_axis DataFrame.reset_index DataFrame.sample DataFrame.select DataFrame.set_index DataFrame.tail DataFrame.take DataFrame.truncate
DataFrame.dropna DataFrame.fillna DataFrame.replace
DataFrame.pivot DataFrame.reorder_levels DataFrame.sort_values DataFrame.sort_index DataFrame.nlargest DataFrame.nsmallest DataFrame.swaplevel DataFrame.stack DataFrame.unstack DataFrame.melt DataFrame.T DataFrame.to_panel DataFrame.to_xarray DataFrame.transpose
DataFrame.append DataFrame.assign DataFrame.join DataFrame.merge DataFrame.update
DataFrame.asfreq DataFrame.asof DataFrame.shift DataFrame.first_valid_index DataFrame.last_valid_index DataFrame.resample DataFrame.to_period DataFrame.to_timestamp DataFrame.tz_convert DataFrame.tz_localize
DataFrame.plot is both a callable method and a namespace attribute for specific plotting methods of the form DataFrame.plot.<kind>.
DataFrame.plot
DataFrame.plot.area DataFrame.plot.bar DataFrame.plot.barh DataFrame.plot.box DataFrame.plot.density DataFrame.plot.hexbin DataFrame.plot.hist DataFrame.plot.kde DataFrame.plot.line DataFrame.plot.pie DataFrame.plot.scatter
DataFrame.boxplot DataFrame.hist
DataFrame.from_csv DataFrame.from_dict DataFrame.from_items DataFrame.from_records DataFrame.info DataFrame.to_pickle DataFrame.to_csv DataFrame.to_hdf DataFrame.to_sql DataFrame.to_dict DataFrame.to_excel DataFrame.to_json DataFrame.to_html DataFrame.to_feather DataFrame.to_latex DataFrame.to_stata DataFrame.to_msgpack DataFrame.to_gbq DataFrame.to_records DataFrame.to_sparse DataFrame.to_dense DataFrame.to_string DataFrame.to_clipboard
SparseDataFrame.to_coo
Panel
Axes
- items: axis 0; each item corresponds to a DataFrame contained inside
- major_axis: axis 1; the index (rows) of each of the DataFrames
- minor_axis: axis 2; the columns of each of the DataFrames
Panel.values Panel.axes Panel.ndim Panel.size Panel.shape Panel.dtypes Panel.ftypes Panel.get_dtype_counts Panel.get_ftype_counts
Panel.astype Panel.copy Panel.isnull Panel.notnull
Panel.get_value Panel.set_value
Panel.at Panel.iat Panel.loc Panel.iloc Panel.__iter__ Panel.iteritems Panel.pop Panel.xs Panel.major_xs Panel.minor_xs
For more information on .at, .iat, .loc, and .iloc, see the indexing documentation <indexing>.
Panel.add Panel.sub Panel.mul Panel.div Panel.truediv Panel.floordiv Panel.mod Panel.pow Panel.radd Panel.rsub Panel.rmul Panel.rdiv Panel.rtruediv Panel.rfloordiv Panel.rmod Panel.rpow Panel.lt Panel.gt Panel.le Panel.ge Panel.ne Panel.eq
Panel.apply Panel.groupby
Panel.abs Panel.clip Panel.clip_lower Panel.clip_upper Panel.count Panel.cummax Panel.cummin Panel.cumprod Panel.cumsum Panel.max Panel.mean Panel.median Panel.min Panel.pct_change Panel.prod Panel.sem Panel.skew Panel.sum Panel.std Panel.var
Panel.add_prefix Panel.add_suffix Panel.drop Panel.equals Panel.filter Panel.first Panel.last Panel.reindex Panel.reindex_axis Panel.reindex_like Panel.rename Panel.sample Panel.select Panel.take Panel.truncate
Panel.dropna Panel.fillna
Panel.sort_index Panel.swaplevel Panel.transpose Panel.swapaxes Panel.conform
Panel.join Panel.update
Panel.asfreq Panel.shift Panel.resample Panel.tz_convert Panel.tz_localize
Panel.from_dict Panel.to_pickle Panel.to_excel Panel.to_hdf Panel.to_sparse Panel.to_frame Panel.to_xarray Panel.to_clipboard
Many of these methods or variants thereof are available on the objects that contain an index (Series/Dataframe) and those should most likely be used before calling these methods directly.
Index
Index.values Index.is_monotonic Index.is_monotonic_increasing Index.is_monotonic_decreasing Index.is_unique Index.has_duplicates Index.dtype Index.inferred_type Index.is_all_dates Index.shape Index.nbytes Index.ndim Index.size Index.empty Index.strides Index.itemsize Index.base Index.T Index.memory_usage
Index.all Index.any Index.argmin Index.argmax Index.copy Index.delete Index.drop Index.drop_duplicates Index.duplicated Index.equals Index.factorize Index.identical Index.insert Index.min Index.max Index.reindex Index.repeat Index.where Index.take Index.putmask Index.set_names Index.unique Index.nunique Index.value_counts
Index.fillna Index.dropna Index.isnull Index.notnull
Index.astype Index.tolist Index.to_datetime Index.to_series
Index.argsort Index.sort_values
Index.shift
Index.append Index.join Index.intersection Index.union Index.difference Index.symmetric_difference
Index.get_indexer Index.get_indexer_non_unique Index.get_level_values Index.get_loc Index.get_value Index.isin Index.slice_indexer Index.slice_locs
CategoricalIndex
CategoricalIndex.codes CategoricalIndex.categories CategoricalIndex.ordered CategoricalIndex.rename_categories CategoricalIndex.reorder_categories CategoricalIndex.add_categories CategoricalIndex.remove_categories CategoricalIndex.remove_unused_categories CategoricalIndex.set_categories CategoricalIndex.as_ordered CategoricalIndex.as_unordered
IntervalIndex
IntervalIndex.from_arrays IntervalIndex.from_tuples IntervalIndex.from_breaks IntervalIndex.from_intervals
MultiIndex IndexSlice
MultiIndex.from_arrays MultiIndex.from_tuples MultiIndex.from_product MultiIndex.set_levels MultiIndex.set_labels MultiIndex.to_hierarchical MultiIndex.to_frame MultiIndex.is_lexsorted MultiIndex.droplevel MultiIndex.swaplevel MultiIndex.reorder_levels MultiIndex.remove_unused_levels
DatetimeIndex
DatetimeIndex.year DatetimeIndex.month DatetimeIndex.day DatetimeIndex.hour DatetimeIndex.minute DatetimeIndex.second DatetimeIndex.microsecond DatetimeIndex.nanosecond DatetimeIndex.date DatetimeIndex.time DatetimeIndex.dayofyear DatetimeIndex.weekofyear DatetimeIndex.week DatetimeIndex.dayofweek DatetimeIndex.weekday DatetimeIndex.weekday_name DatetimeIndex.quarter DatetimeIndex.tz DatetimeIndex.freq DatetimeIndex.freqstr DatetimeIndex.is_month_start DatetimeIndex.is_month_end DatetimeIndex.is_quarter_start DatetimeIndex.is_quarter_end DatetimeIndex.is_year_start DatetimeIndex.is_year_end DatetimeIndex.is_leap_year DatetimeIndex.inferred_freq
DatetimeIndex.indexer_at_time DatetimeIndex.indexer_between_time
DatetimeIndex.normalize DatetimeIndex.strftime DatetimeIndex.snap DatetimeIndex.tz_convert DatetimeIndex.tz_localize DatetimeIndex.round DatetimeIndex.floor DatetimeIndex.ceil
DatetimeIndex.to_datetime DatetimeIndex.to_period DatetimeIndex.to_perioddelta DatetimeIndex.to_pydatetime DatetimeIndex.to_series
TimedeltaIndex
TimedeltaIndex.days TimedeltaIndex.seconds TimedeltaIndex.microseconds TimedeltaIndex.nanoseconds TimedeltaIndex.components TimedeltaIndex.inferred_freq
TimedeltaIndex.to_pytimedelta TimedeltaIndex.to_series TimedeltaIndex.round TimedeltaIndex.floor TimedeltaIndex.ceil
pandas.core.window
Rolling objects are returned by .rolling calls: pandas.DataFrame.rolling, pandas.Series.rolling, etc. Expanding objects are returned by .expanding calls: pandas.DataFrame.expanding, pandas.Series.expanding, etc. EWM objects are returned by .ewm calls: pandas.DataFrame.ewm, pandas.Series.ewm, etc.
pandas.core.window
Rolling.count Rolling.sum Rolling.mean Rolling.median Rolling.var Rolling.std Rolling.min Rolling.max Rolling.corr Rolling.cov Rolling.skew Rolling.kurt Rolling.apply Rolling.quantile Window.mean Window.sum
pandas.core.window
Expanding.count Expanding.sum Expanding.mean Expanding.median Expanding.var Expanding.std Expanding.min Expanding.max Expanding.corr Expanding.cov Expanding.skew Expanding.kurt Expanding.apply Expanding.quantile
pandas.core.window
EWM.mean EWM.std EWM.var EWM.corr EWM.cov
pandas.core.groupby
GroupBy objects are returned by groupby calls: pandas.DataFrame.groupby, pandas.Series.groupby, etc.
GroupBy.__iter__ GroupBy.groups GroupBy.indices GroupBy.get_group
pandas
Grouper
pandas.core.groupby
GroupBy.apply GroupBy.aggregate GroupBy.transform
GroupBy.count GroupBy.cumcount GroupBy.first GroupBy.head GroupBy.last GroupBy.max GroupBy.mean GroupBy.median GroupBy.min GroupBy.nth GroupBy.ohlc GroupBy.prod GroupBy.size GroupBy.sem GroupBy.std GroupBy.sum GroupBy.var GroupBy.tail
The following methods are available in both SeriesGroupBy and DataFrameGroupBy objects, but may differ slightly, usually in that the DataFrameGroupBy version usually permits the specification of an axis argument, and often an argument indicating whether to restrict application to columns of a specific data type.
DataFrameGroupBy.agg DataFrameGroupBy.all DataFrameGroupBy.any DataFrameGroupBy.bfill DataFrameGroupBy.corr DataFrameGroupBy.count DataFrameGroupBy.cov DataFrameGroupBy.cummax DataFrameGroupBy.cummin DataFrameGroupBy.cumprod DataFrameGroupBy.cumsum DataFrameGroupBy.describe DataFrameGroupBy.diff DataFrameGroupBy.ffill DataFrameGroupBy.fillna DataFrameGroupBy.hist DataFrameGroupBy.idxmax DataFrameGroupBy.idxmin DataFrameGroupBy.mad DataFrameGroupBy.pct_change DataFrameGroupBy.plot DataFrameGroupBy.quantile DataFrameGroupBy.rank DataFrameGroupBy.resample DataFrameGroupBy.shift DataFrameGroupBy.size DataFrameGroupBy.skew DataFrameGroupBy.take DataFrameGroupBy.tshift
The following methods are available only for SeriesGroupBy objects.
SeriesGroupBy.nlargest SeriesGroupBy.nsmallest SeriesGroupBy.nunique SeriesGroupBy.unique SeriesGroupBy.value_counts
The following methods are available only for DataFrameGroupBy objects.
DataFrameGroupBy.corrwith DataFrameGroupBy.boxplot
pandas.core.resample
Resampler objects are returned by resample calls: pandas.DataFrame.resample, pandas.Series.resample.
Resampler.__iter__ Resampler.groups Resampler.indices Resampler.get_group
Resampler.apply Resampler.aggregate Resampler.transform
Resampler.ffill Resampler.backfill Resampler.bfill Resampler.pad Resampler.fillna Resampler.asfreq Resampler.interpolate
Resampler.count Resampler.nunique Resampler.first Resampler.last Resampler.max Resampler.mean Resampler.median Resampler.min Resampler.ohlc Resampler.prod Resampler.size Resampler.sem Resampler.std Resampler.sum Resampler.var
pandas.io.formats.style
Styler objects are returned by pandas.DataFrame.style.
Styler
Styler.apply Styler.applymap Styler.format Styler.set_precision Styler.set_table_styles Styler.set_caption Styler.set_properties Styler.set_uuid Styler.clear
Styler.highlight_max Styler.highlight_min Styler.highlight_null Styler.background_gradient Styler.bar
Styler.render Styler.export Styler.use
pandas
describe_option reset_option get_option set_option option_context
testing.assert_frame_equal testing.assert_series_equal testing.assert_index_equal
errors.DtypeWarning errors.EmptyDataError errors.OutOfBoundsDatetime errors.ParserError errors.ParserWarning errors.PerformanceWarning errors.UnsortedIndexError errors.UnsupportedFunctionCall
api.types.union_categoricals api.types.infer_dtype api.types.pandas_dtype
Dtype introspection
api.types.is_bool_dtype api.types.is_categorical_dtype api.types.is_complex_dtype api.types.is_datetime64_any_dtype api.types.is_datetime64_dtype api.types.is_datetime64_ns_dtype api.types.is_datetime64tz_dtype api.types.is_extension_type api.types.is_float_dtype api.types.is_int64_dtype api.types.is_integer_dtype api.types.is_interval_dtype api.types.is_numeric_dtype api.types.is_object_dtype api.types.is_period_dtype api.types.is_signed_integer_dtype api.types.is_string_dtype api.types.is_timedelta64_dtype api.types.is_timedelta64_ns_dtype api.types.is_unsigned_integer_dtype api.types.is_sparse
Iterable introspection
api.types.is_dict_like api.types.is_file_like api.types.is_list_like api.types.is_named_tuple api.types.is_iterator
Scalar introspection
api.types.is_bool api.types.is_categorical api.types.is_complex api.types.is_datetimetz api.types.is_float api.types.is_hashable api.types.is_integer api.types.is_interval api.types.is_number api.types.is_period api.types.is_re api.types.is_re_compilable api.types.is_scalar