Series.tshift(periods=1, freq=None, axis=0) [source] Shift the time index, using the index?s frequency if available. Parameters: periods : int Number of periods to move, can be positive or negative freq : DateOffset, timedelta, or time rule string, default None Increment to use from the tseries module or time rule (e.g. ?EOM?) axis : int or basestring Corresponds to the axis that contains the Index Returns: shifted : NDFrame Notes If freq is not specified then tries to use the fre

DataFrame.first(offset) [source] Convenience method for subsetting initial periods of time series data based on a date offset. Parameters: offset : string, DateOffset, dateutil.relativedelta Returns: subset : type of caller Examples ts.first(?10D?) -> First 10 days

Index.holds_integer() [source]

DataFrame.rsub(other, axis='columns', level=None, fill_value=None) [source] Subtraction of dataframe and other, element-wise (binary operator rsub). Equivalent to other - dataframe, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other : Series, DataFrame, or constant axis : {0, 1, ?index?, ?columns?} For Series input, axis to match Series index on fill_value : None or float value, default None Fill missing (NaN) values with this value. If

class pandas.TimedeltaIndex [source] Immutable ndarray of timedelta64 data, represented internally as int64, and which can be boxed to timedelta objects Parameters: data : array-like (1-dimensional), optional Optional timedelta-like data to construct index with unit: unit of the arg (D,h,m,s,ms,us,ns) denote the unit, optional which is an integer/float number freq: a frequency for the index, optional copy : bool Make a copy of input ndarray start : starting value, timedelta-like, opt

Panel.get_values() [source] same as values (but handles sparseness conversions)

Series.nbytes return the number of bytes in the underlying data

DataFrame.assign(**kwargs) [source] Assign new columns to a DataFrame, returning a new object (a copy) with all the original columns in addition to the new ones. New in version 0.16.0. Parameters: kwargs : keyword, value pairs keywords are the column names. If the values are callable, they are computed on the DataFrame and assigned to the new columns. The callable must not change input DataFrame (though pandas doesn?t check it). If the values are not callable, (e.g. a Series, scalar, or

CategoricalIndex.dtype_str = None

MultiIndex.is_(other) [source] More flexible, faster check like is but that works through views Note: this is not the same as Index.identical(), which checks that metadata is also the same. Parameters: other : object other object to compare against. Returns: True if both have same underlying data, False otherwise : bool