Expanding.min(*args, **kwargs) [source] expanding minimum Parameters: how : string, default ?min? (DEPRECATED) Method for down- or re-sampling Returns: same type as input See also pandas.Series.expanding, pandas.DataFrame.expanding

Expanding.median(**kwargs) [source] expanding median Parameters: how : string, default ?median? (DEPRECATED) Method for down- or re-sampling Returns: same type as input See also pandas.Series.expanding, pandas.DataFrame.expanding

Expanding.mean(*args, **kwargs) [source] expanding mean Parameters: how : string, default None (DEPRECATED) Method for down- or re-sampling Returns: same type as input See also pandas.Series.expanding, pandas.DataFrame.expanding

Expanding.max(*args, **kwargs) [source] expanding maximum Parameters: how : string, default ?max? (DEPRECATED) Method for down- or re-sampling Returns: same type as input See also pandas.Series.expanding, pandas.DataFrame.expanding

Expanding.kurt(**kwargs) [source] Unbiased expanding kurtosis Returns: same type as input See also pandas.Series.expanding, pandas.DataFrame.expanding

Expanding.cov(other=None, pairwise=None, ddof=1, **kwargs) [source] expanding sample covariance Parameters: other : Series, DataFrame, or ndarray, optional if not supplied then will default to self and produce pairwise output pairwise : bool, default None If False then only matching columns between self and other will be used and the output will be a DataFrame. If True then all pairwise combinations will be calculated and the output will be a Panel in the case of DataFrame inputs. In th

Expanding.count(**kwargs) [source] expanding count of number of non-NaN observations inside provided window. Returns: same type as input See also pandas.Series.expanding, pandas.DataFrame.expanding

Expanding.corr(other=None, pairwise=None, **kwargs) [source] expanding sample correlation Parameters: other : Series, DataFrame, or ndarray, optional if not supplied then will default to self and produce pairwise output pairwise : bool, default None If False then only matching columns between self and other will be used and the output will be a DataFrame. If True then all pairwise combinations will be calculated and the output will be a Panel in the case of DataFrame inputs. In the case

Expanding.apply(func, args=(), kwargs={}) [source] expanding function apply Parameters: func : function Must produce a single value from an ndarray input *args and **kwargs are passed to the function Returns: same type as input See also pandas.Series.expanding, pandas.DataFrame.expanding

ExcelFile.parse(sheetname=0, header=0, skiprows=None, skip_footer=0, names=None, index_col=None, parse_cols=None, parse_dates=False, date_parser=None, na_values=None, thousands=None, convert_float=True, has_index_names=None, converters=None, true_values=None, false_values=None, squeeze=False, **kwds) [source] Parse specified sheet(s) into a DataFrame Equivalent to read_excel(ExcelFile, ...) See the read_excel docstring for more info on accepted parameters