Panel.to_sql(name, con, flavor=None, schema=None, if_exists='fail', index=True, index_label=None, chunksize=None, dtype=None) [source] Write records stored in a DataFrame to a SQL database. Parameters: name : string Name of SQL table con : SQLAlchemy engine or DBAPI2 connection (legacy mode) Using SQLAlchemy makes it possible to use any DB supported by that library. If a DBAPI2 object, only sqlite3 is supported. flavor : ?sqlite?, default None DEPRECATED: this parameter will be remove

CategoricalIndex.set_names(names, level=None, inplace=False) [source] Set new names on index. Defaults to returning new index. Parameters: names : str or sequence name(s) to set level : int, level name, or sequence of int/level names (default None) If the index is a MultiIndex (hierarchical), level(s) to set (None for all levels). Otherwise level must be None inplace : bool if True, mutates in place Returns: new index (of same type and class...etc) [if inplace, returns None] Examp

DatetimeIndex.intersection(other) [source] Specialized intersection for DatetimeIndex objects. May be much faster than Index.intersection Parameters: other : DatetimeIndex or array-like Returns: y : Index or DatetimeIndex

Panel.add(other, axis=0) [source] Addition of series and other, element-wise (binary operator add). Equivalent to panel + other. Parameters: other : DataFrame or Panel axis : {items, major_axis, minor_axis} Axis to broadcast over Returns: Panel See also Panel.radd

Resampler.size(_method='size') [source] Compute group sizes See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby

DataFrameGroupBy.all(axis=None, bool_only=None, skipna=None, level=None, **kwargs) Return whether all elements are True over requested axis Parameters: axis : {index (0), columns (1)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA level : int or level name, default None If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series bool_only : boolean, default None Include only boolean c

Resampler.sum(_method='sum', *args, **kwargs) [source] Compute sum of group values See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby

DataFrameGroupBy.pct_change(periods=1, fill_method='pad', limit=None, freq=None, **kwargs) Percent change over given number of periods. Parameters: periods : int, default 1 Periods to shift for forming percent change fill_method : str, default ?pad? How to handle NAs before computing percent changes limit : int, default None The number of consecutive NAs to fill before stopping freq : DateOffset, timedelta, or offset alias string, optional Increment to use from time series API (e.g.

Index.dropna(how='any') [source] Return Index without NA/NaN values Parameters: how : {?any?, ?all?}, default ?any? If the Index is a MultiIndex, drop the value when any or all levels are NaN. Returns: valid : Index

Panel4D.describe(percentiles=None, include=None, exclude=None) [source] Generate various summary statistics, excluding NaN values. Parameters: percentiles : array-like, optional The percentiles to include in the output. Should all be in the interval [0, 1]. By default percentiles is [.25, .5, .75], returning the 25th, 50th, and 75th percentiles. include, exclude : list-like, ?all?, or None (default) Specify the form of the returned result. Either: None to both (default). The result will