DataFrame.rolling(window, min_periods=None, freq=None, center=False, win_type=None, on=None, axis=0) [source] Provides rolling window calculcations. New in version 0.18.0. Parameters: window : int, or offset Size of the moving window. This is the number of observations used for calculating the statistic. Each window will be a fixed size. If its an offset then this will be the time period of each window. Each window will be a variable sized based on the observations included in the time-

MultiIndex.format(space=2, sparsify=None, adjoin=True, names=False, na_rep=None, formatter=None) [source]

Series.dt.weekday_name The name of day in a week (ex: Friday) New in version 0.18.1.

Panel.head(n=5) [source]

pandas.read_sql(sql, con, index_col=None, coerce_float=True, params=None, parse_dates=None, columns=None, chunksize=None) [source] Read SQL query or database table into a DataFrame. Parameters: sql : string SQL query or SQLAlchemy Selectable (select or text object) to be executed, or database table name. con : SQLAlchemy connectable(engine/connection) or database string URI or DBAPI2 connection (fallback mode) Using SQLAlchemy makes it possible to use any DB supported by that library. I

Panel4D.ndim Number of axes / array dimensions

Series.flags

pandas.merge_asof(left, right, on=None, left_on=None, right_on=None, left_index=False, right_index=False, by=None, left_by=None, right_by=None, suffixes=('_x', '_y'), tolerance=None, allow_exact_matches=True) [source] Perform an asof merge. This is similar to a left-join except that we match on nearest key rather than equal keys. For each row in the left DataFrame, we select the last row in the right DataFrame whose ?on? key is less than or equal to the left?s key. Both DataFrames must be s

Series.iat Fast integer location scalar accessor. Similarly to iloc, iat provides integer based lookups. You can also set using these indexers.

SeriesGroupBy.value_counts(normalize=False, sort=True, ascending=False, bins=None, dropna=True) [source]