TimedeltaIndex.value_counts(normalize=False, sort=True, ascending=False, bins=None, dropna=True) [source] Returns object containing counts of unique values. The resulting object will be in descending order so that the first element is the most frequently-occurring element. Excludes NA values by default. Parameters: normalize : boolean, default False If True then the object returned will contain the relative frequencies of the unique values. sort : boolean, default True Sort by values a

TimedeltaIndex.values return the underlying data as an ndarray

Rolling.skew(**kwargs) [source] Unbiased rolling skewness Returns: same type as input See also pandas.Series.rolling, pandas.DataFrame.rolling

TimedeltaIndex.putmask(mask, value) [source] return a new Index of the values set with the mask See also numpy.ndarray.putmask

DataFrame.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 wi

Index.names

DataFrame.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 re

Panel4D.reindex_like(other, method=None, copy=True, limit=None, tolerance=None) [source] Return an object with matching indices to myself. Parameters: other : Object method : string or None copy : boolean, default True limit : int, default None Maximum number of consecutive labels to fill for inexact matches. tolerance : optional Maximum distance between labels of the other object and this object for inexact matches. New in version 0.17.0. Returns: reindexed : same as input Notes

Series.cumsum(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative sum over requested axis. Parameters: axis : {index (0)} skipna : boolean, default True Exclude NA/null values. If an entire row/column is NA, the result will be NA Returns: cumsum : scalar

Series.swapaxes(axis1, axis2, copy=True) [source] Interchange axes and swap values axes appropriately Returns: y : same as input