Panel.get(key, default=None) [source] Get item from object for given key (DataFrame column, Panel slice, etc.). Returns default value if not found. Parameters: key : object Returns: value : type of items contained in object

DataFrameGroupBy.count() [source] Compute count of group, excluding missing values

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

MultiIndex.delete(loc) [source] Make new index with passed location deleted Returns: new_index : MultiIndex

DataFrame.insert(loc, column, value, allow_duplicates=False) [source] Insert column into DataFrame at specified location. If allow_duplicates is False, raises Exception if column is already contained in the DataFrame. Parameters: loc : int Must have 0 <= loc <= len(columns) column : object value : scalar, Series, or array-like

DataFrame.tz_localize(*args, **kwargs) [source] Localize tz-naive TimeSeries to target time zone. Parameters: tz : string or pytz.timezone object axis : the axis to localize level : int, str, default None If axis ia a MultiIndex, localize a specific level. Otherwise must be None copy : boolean, default True Also make a copy of the underlying data ambiguous : ?infer?, bool-ndarray, ?NaT?, default ?raise? ?infer? will attempt to infer fall dst-transition hours based on order bool-ndarra

GroupBy.ohlc() [source] Compute sum of values, excluding missing values For multiple groupings, the result index will be a MultiIndex See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby

GroupBy.std(ddof=1, *args, **kwargs) [source] Compute standard deviation of groups, excluding missing values For multiple groupings, the result index will be a MultiIndex Parameters: ddof : integer, default 1 degrees of freedom See also pandas.Series.groupby, pandas.DataFrame.groupby, pandas.Panel.groupby

Index.get_values() [source] return the underlying data as an ndarray

pandas.io.gbq.read_gbq(query, project_id=None, index_col=None, col_order=None, reauth=False, verbose=True, private_key=None, dialect='legacy') [source] Load data from Google BigQuery. THIS IS AN EXPERIMENTAL LIBRARY The main method a user calls to execute a Query in Google BigQuery and read results into a pandas DataFrame. Google BigQuery API Client Library v2 for Python is used. Documentation is available at https://developers.google.com/api-client-library/python/apis/bigquery/v2 Authentic