Series.isnull() [source] Return a boolean same-sized object indicating if the values are null. See also notnull boolean inverse of isnull

Series.clip_upper(threshold, axis=None) [source] Return copy of input with values above 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

DataFrame.slice_shift(periods=1, axis=0) [source] Equivalent to shift without copying data. The shifted data will not include the dropped periods and the shifted axis will be smaller than the original. Parameters: periods : int Number of periods to move, can be positive or negative Returns: shifted : same type as caller Notes While the slice_shift is faster than shift, you may pay for it later during alignment.

DataFrameGroupBy.take(indices, axis=0, convert=True, is_copy=True, **kwargs) Analogous to ndarray.take Parameters: indices : list / array of ints axis : int, default 0 convert : translate neg to pos indices (default) is_copy : mark the returned frame as a copy Returns: taken : type of caller

Panel.rmod(other, axis=0) [source] Modulo of series and other, element-wise (binary operator rmod). Equivalent to other % panel. Parameters: other : DataFrame or Panel axis : {items, major_axis, minor_axis} Axis to broadcast over Returns: Panel See also Panel.mod

CategoricalIndex.shift(periods=1, freq=None) [source] Shift Index containing datetime objects by input number of periods and DateOffset Returns: shifted : Index

DatetimeIndex.is_monotonic_increasing return if the index is monotonic increasing (only equal or increasing) values.

DatetimeIndex.floor(freq) [source] floor the index to the specified freq Parameters: freq : freq string/object Returns: index of same type Raises: ValueError if the freq cannot be converted

CategoricalIndex.sym_diff(*args, **kwargs) [source]

CategoricalIndex.take(indices, axis=0, allow_fill=True, fill_value=None, **kwargs) [source] return a new %(klass)s of the values selected by the indices For internal compatibility with numpy arrays. Parameters: indices : list Indices to be taken axis : int, optional The axis over which to select values, always 0. allow_fill : bool, default True fill_value : bool, default None If allow_fill=True and fill_value is not None, indices specified by -1 is regarded as NA. If Index doesn?t hol