DataFrame.get_value(index, col, takeable=False) [source] Quickly retrieve single value at passed column and index Parameters: index : row label col : column label takeable : interpret the index/col as indexers, default False Returns: value : scalar value

DataFrame.as_matrix(columns=None) [source] Convert the frame to its Numpy-array representation. Parameters: columns: list, optional, default:None If None, return all columns, otherwise, returns specified columns. Returns: values : ndarray If the caller is heterogeneous and contains booleans or objects, the result will be of dtype=object. See Notes. See also pandas.DataFrame.values Notes Return is NOT a Numpy-matrix, rather, a Numpy-array. The dtype will be a lower-common-denominat

EWM.var(bias=False, *args, **kwargs) [source] exponential weighted moving variance Parameters: bias : boolean, default False Use a standard estimation bias correction Returns: same type as input See also pandas.Series.ewm, pandas.DataFrame.ewm

DataFrame.duplicated(*args, **kwargs) [source] Return boolean Series denoting duplicate rows, optionally only considering certain columns Parameters: subset : column label or sequence of labels, optional Only consider certain columns for identifying duplicates, by default use all of the columns keep : {?first?, ?last?, False}, default ?first? first : Mark duplicates as True except for the first occurrence. last : Mark duplicates as True except for the last occurrence. False : Mark all

Panel4D.clip_lower(threshold, axis=None) [source] Return copy of the input with values below given value(s) truncated. Parameters: threshold : float or array_like axis : int or string axis name, optional Align object with threshold along the given axis. Returns: clipped : same type as input See also clip

Panel4D.tz_convert(tz, axis=0, level=None, copy=True) [source] Convert tz-aware axis to target time zone. Parameters: tz : string or pytz.timezone object axis : the axis to convert level : int, str, default None If axis ia a MultiIndex, convert a specific level. Otherwise must be None copy : boolean, default True Also make a copy of the underlying data Raises: TypeError If the axis is tz-naive.

Index.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 ascending

MultiIndex.slice_indexer(start=None, end=None, step=None, kind=None) [source] For an ordered Index, compute the slice indexer for input labels and step Parameters: start : label, default None If None, defaults to the beginning end : label, default None If None, defaults to the end step : int, default None kind : string, default None Returns: indexer : ndarray or slice Notes This function assumes that the data is sorted, so use at your own peril

Panel4D.sort_index(axis=0, level=None, ascending=True, inplace=False, kind='quicksort', na_position='last', sort_remaining=True) [source] Sort object by labels (along an axis) Parameters: axis : axes to direct sorting level : int or level name or list of ints or list of level names if not None, sort on values in specified index level(s) ascending : boolean, default True Sort ascending vs. descending inplace : bool, default False if True, perform operation in-place kind : {?quicksort?

Panel4D.count(axis='major') [source] Return number of observations over requested axis. Parameters: axis : {?items?, ?major?, ?minor?} or {0, 1, 2} Returns: count : DataFrame