Grouper.ax

Series.convert_objects(convert_dates=True, convert_numeric=False, convert_timedeltas=True, copy=True) [source] Deprecated. Attempt to infer better dtype for object columns Parameters: convert_dates : boolean, default True If True, convert to date where possible. If ?coerce?, force conversion, with unconvertible values becoming NaT. convert_numeric : boolean, default False If True, attempt to coerce to numbers (including strings), with unconvertible values becoming NaN. convert_timedelt

DataFrame.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.

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

DataFrame.kurtosis(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return unbiased kurtosis over requested axis using Fisher?s definition of kurtosis (kurtosis of normal == 0.0). Normalized by N-1 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 particular level,

Series.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

Panel4D.pipe(func, *args, **kwargs) [source] Apply func(self, *args, **kwargs) New in version 0.16.2. Parameters: func : function function to apply to the NDFrame. args, and kwargs are passed into func. Alternatively a (callable, data_keyword) tuple where data_keyword is a string indicating the keyword of callable that expects the NDFrame. args : positional arguments passed into func. kwargs : a dictionary of keyword arguments passed into func. Returns: object : the return type of fu

Panel.median(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) [source] Return the median of the values for the requested axis Parameters: axis : {items (0), major_axis (1), minor_axis (2)} 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 particular level, collapsing into a DataFrame numeric_only : boolean, default N

DataFrame.plot.bar(x=None, y=None, **kwds) [source] Vertical bar plot New in version 0.17.0. Parameters: x, y : label or position, optional Coordinates for each point. **kwds : optional Keyword arguments to pass on to pandas.DataFrame.plot(). Returns: axes : matplotlib.AxesSubplot or np.array of them

DataFrame.sub(other, axis='columns', level=None, fill_value=None) [source] Subtraction of dataframe and other, element-wise (binary operator sub). Equivalent to dataframe - other, 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 bo