Series.to_string(buf=None, na_rep='NaN', float_format=None, header=True, index=True, length=False, dtype=False, name=False, max_rows=None) [source] Render a string representation of the Series Parameters: buf : StringIO-like, optional buffer to write to na_rep : string, optional string representation of NAN to use, default ?NaN? float_format : one-parameter function, optional formatter function to apply to columns? elements if they are floats default None header: boolean, default Tru

Series.set_value(label, value, takeable=False) [source] Quickly set single value at passed label. If label is not contained, a new object is created with the label placed at the end of the result index Parameters: label : object Partial indexing with MultiIndex not allowed value : object Scalar value takeable : interpret the index as indexers, default False Returns: series : Series If label is contained, will be reference to calling Series, otherwise a new object

Resampler.get_group(name, obj=None) [source] Constructs NDFrame from group with provided name Parameters: name : object the name of the group to get as a DataFrame obj : NDFrame, default None the NDFrame to take the DataFrame out of. If it is None, the object groupby was called on will be used Returns: group : type of obj

Panel4D.ix A primarily label-location based indexer, with integer position fallback. .ix[] supports mixed integer and label based access. It is primarily label based, but will fall back to integer positional access unless the corresponding axis is of integer type. .ix is the most general indexer and will support any of the inputs in .loc and .iloc. .ix also supports floating point label schemes. .ix is exceptionally useful when dealing with mixed positional and label based hierachical index

DataFrame.div(other, axis='columns', level=None, fill_value=None) [source] Floating division of dataframe and other, element-wise (binary operator truediv). Equivalent to dataframe / other, but with support to substitute a fill_value for missing data in one of the inputs. Parameters: other : Series, DataFrame, or constant axis : {0, 1, ?index?, ?columns?} For Series input, axis to match Series index on fill_value : None or float value, default None Fill missing (NaN) values with this va

Series.ravel(order='C') [source] Return the flattened underlying data as an ndarray See also numpy.ndarray.ravel

Panel.astype(dtype, copy=True, raise_on_error=True, **kwargs) [source] Cast object to input numpy.dtype Return a copy when copy = True (be really careful with this!) Parameters: dtype : data type, or dict of column name -> data type Use a numpy.dtype or Python type to cast entire pandas object to the same type. Alternatively, use {col: dtype, ...}, where col is a column label and dtype is a numpy.dtype or Python type to cast one or more of the DataFrame?s columns to column-specific typ

Panel4D.floordiv(other, axis=0) [source] Integer division of series and other, element-wise (binary operator floordiv). Equivalent to panel // other. Parameters: other : Panel or Panel4D axis : {labels, items, major_axis, minor_axis} Axis to broadcast over Returns: Panel4D See also Panel4D.rfloordiv

Series.append(to_append, ignore_index=False, verify_integrity=False) [source] Concatenate two or more Series. Parameters: to_append : Series or list/tuple of Series ignore_index : boolean, default False If True, do not use the index labels. verify_integrity : boolean, default False If True, raise Exception on creating index with duplicates Returns: appended : Series Examples >>> s1 = pd.Series([1, 2, 3]) >>> s2 = pd.Series([4, 5, 6]) >>> s3 = pd.Series([4,

DataFrame.eval(expr, inplace=None, **kwargs) [source] Evaluate an expression in the context of the calling DataFrame instance. Parameters: expr : string The expression string to evaluate. inplace : bool If the expression contains an assignment, whether to return a new DataFrame or mutate the existing. WARNING: inplace=None currently falls back to to True, but in a future version, will default to False. Use inplace=True explicitly rather than relying on the default. New in version 0.18.