Index.union(other) [source] Form the union of two Index objects and sorts if possible. Parameters: other : Index or array-like Returns: union : Index Examples >>> idx1 = pd.Index([1, 2, 3, 4]) >>> idx2 = pd.Index([3, 4, 5, 6]) >>> idx1.union(idx2) Int64Index([1, 2, 3, 4, 5, 6], dtype='int64')

Series.to_csv(path=None, index=True, sep=', ', na_rep='', float_format=None, header=False, index_label=None, mode='w', encoding=None, date_format=None, decimal='.') [source] Write Series to a comma-separated values (csv) file Parameters: path : string or file handle, default None File path or object, if None is provided the result is returned as a string. na_rep : string, default ?? Missing data representation float_format : string, default None Format string for floating point number

Series.to_sql(name, con, flavor=None, schema=None, if_exists='fail', index=True, index_label=None, chunksize=None, dtype=None) [source] Write records stored in a DataFrame to a SQL database. Parameters: name : string Name of SQL table con : SQLAlchemy engine or DBAPI2 connection (legacy mode) Using SQLAlchemy makes it possible to use any DB supported by that library. If a DBAPI2 object, only sqlite3 is supported. flavor : ?sqlite?, default None DEPRECATED: this parameter will be remov

Series.to_msgpack(path_or_buf=None, encoding='utf-8', **kwargs) [source] msgpack (serialize) object to input file path THIS IS AN EXPERIMENTAL LIBRARY and the storage format may not be stable until a future release. Parameters: path : string File path, buffer-like, or None if None, return generated string append : boolean whether to append to an existing msgpack (default is False) compress : type of compressor (zlib or blosc), default to None (no compression)

DataFrameGroupBy.boxplot(grouped, subplots=True, column=None, fontsize=None, rot=0, grid=True, ax=None, figsize=None, layout=None, **kwds) [source] Make box plots from DataFrameGroupBy data. Parameters: grouped : Grouped DataFrame subplots : False - no subplots will be used True - create a subplot for each group column : column name or list of names, or vector Can be any valid input to groupby fontsize : int or string rot : label rotation angle grid : Setting this to True will show th

Panel.cumsum(axis=None, skipna=True, *args, **kwargs) [source] Return cumulative sum over 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 Returns: cumsum : DataFrame

DataFrame.replace(to_replace=None, value=None, inplace=False, limit=None, regex=False, method='pad', axis=None) [source] Replace values given in ?to_replace? with ?value?. Parameters: to_replace : str, regex, list, dict, Series, numeric, or None str or regex: str: string exactly matching to_replace will be replaced with value regex: regexs matching to_replace will be replaced with value list of str, regex, or numeric: First, if to_replace and value are both lists, they must be the

Panel.mad(axis=None, skipna=None, level=None) [source] Return the mean absolute deviation 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 None Include on

Series.ne(other, level=None, fill_value=None, axis=0) [source] Not equal to of series and other, element-wise (binary operator ne). Equivalent to series != other, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other: Series or scalar value fill_value : None or float value, default None (NaN) Fill missing (NaN) values with this value. If both Series are missing, the result will be missing level : int or name Broadcast across a level, matchi

Panel.sem(axis=None, skipna=None, level=None, ddof=1, numeric_only=None, **kwargs) [source] Return unbiased standard error of the mean over requested axis. Normalized by N-1 by default. This can be changed using the ddof argument 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