DataFrame.equals(other) [source] Determines if two NDFrame objects contain the same elements. NaNs in the same location are considered equal.

Series.squeeze(**kwargs) [source] Squeeze length 1 dimensions.

MultiIndex.is_type_compatible(kind) [source]

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

Series.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-denominator

Panel.get_ftype_counts() [source] Return the counts of ftypes in this object.

Series.between_time(start_time, end_time, include_start=True, include_end=True) [source] Select values between particular times of the day (e.g., 9:00-9:30 AM). Parameters: start_time : datetime.time or string end_time : datetime.time or string include_start : boolean, default True include_end : boolean, default True Returns: values_between_time : type of caller

Panel.between_time(start_time, end_time, include_start=True, include_end=True) [source] Select values between particular times of the day (e.g., 9:00-9:30 AM). Parameters: start_time : datetime.time or string end_time : datetime.time or string include_start : boolean, default True include_end : boolean, default True Returns: values_between_time : type of caller

Series.plot.hist(bins=10, **kwds) [source] Histogram New in version 0.17.0. Parameters: bins: integer, default 10 Number of histogram bins to be used **kwds : optional Keyword arguments to pass on to pandas.Series.plot(). Returns: axes : matplotlib.AxesSubplot or np.array of them

Index.insert(loc, item) [source] Make new Index inserting new item at location. Follows Python list.append semantics for negative values Parameters: loc : int item : object Returns: new_index : Index