DataFrame.size number of elements in the NDFrame

DataFrame.shift(periods=1, freq=None, axis=0) [source] Shift index by desired number of periods with an optional time freq Parameters: periods : int Number of periods to move, can be positive or negative freq : DateOffset, timedelta, or time rule string, optional Increment to use from the tseries module or time rule (e.g. ?EOM?). See Notes. axis : {0 or ?index?, 1 or ?columns?} Returns: shifted : DataFrame Notes If freq is specified then the index values are shifted but the data is

DataFrame.set_value(index, col, value, takeable=False) [source] Put single value at passed column and index Parameters: index : row label col : column label value : scalar value takeable : interpret the index/col as indexers, default False Returns: frame : DataFrame If label pair is contained, will be reference to calling DataFrame, otherwise a new object

DataFrame.set_index(keys, drop=True, append=False, inplace=False, verify_integrity=False) [source] Set the DataFrame index (row labels) using one or more existing columns. By default yields a new object. Parameters: keys : column label or list of column labels / arrays drop : boolean, default True Delete columns to be used as the new index append : boolean, default False Whether to append columns to existing index inplace : boolean, default False Modify the DataFrame in place (do not

DataFrame.shape Return a tuple representing the dimensionality of the DataFrame.

DataFrame.set_axis(axis, labels) [source] public verson of axis assignment

DataFrame.sem(axis=None, skipna=None, level=None, ddof=1, numeric_only=None, **kwargs) [source] Return unbiased standard error of the mean over requested axis. Normalized by N-1 by default. This can be changed using the ddof argument 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 particu

DataFrame.select_dtypes(include=None, exclude=None) [source] Return a subset of a DataFrame including/excluding columns based on their dtype. Parameters: include, exclude : list-like A list of dtypes or strings to be included/excluded. You must pass in a non-empty sequence for at least one of these. Returns: subset : DataFrame The subset of the frame including the dtypes in include and excluding the dtypes in exclude. Raises: ValueError If both of include and exclude are empty If

DataFrame.select(crit, axis=0) [source] Return data corresponding to axis labels matching criteria Parameters: crit : function To be called on each index (label). Should return True or False axis : int Returns: selection : type of caller

DataFrame.sample(n=None, frac=None, replace=False, weights=None, random_state=None, axis=None) [source] Returns a random sample of items from an axis of object. New in version 0.16.1. Parameters: n : int, optional Number of items from axis to return. Cannot be used with frac. Default = 1 if frac = None. frac : float, optional Fraction of axis items to return. Cannot be used with n. replace : boolean, optional Sample with or without replacement. Default = False. weights : str or nda