between_time can now select times across midnight (GH1871) • Series constructor can now handle generator as input (GH1679) • DataFrame.dropna can now take multiple axes (tuple/list) as input (GH924) axis=1) Out[94]: col2 0 2 1 3 2 4 Finally, one can also set a seed for sample‘s random number generator using the random_state argument, which will accept either an integer (as a seed) or a numpy RandomState Note: In python 2 replacing the range with its generator counterpart (xrange) would mean the range line would vanish. In python 3 range is already a generator. 26.1.2 Plain cython First we’re going to need

between_time can now select times across midnight (GH1871) • Series constructor can now handle generator as input (GH1679) • DataFrame.dropna can now take multiple axes (tuple/list) as input (GH924) Note: In python 2 replacing the range with its generator counterpart (xrange) would mean the range line would vanish. In python 3 range is already a generator. 19.1.2 Plain cython First we’re going to need DataFrame.iterrows() Iterate over rows of DataFrame as (index, Series) pairs. Returns it : generator A generator that iterates over the rows of the frame. Notes •iterrows does not preserve dtypes across

between_time can now select times across midnight (GH1871) • Series constructor can now handle generator as input (GH1679) • DataFrame.dropna can now take multiple axes (tuple/list) as input (GH924) Note: In python 2 replacing the range with its generator counterpart (xrange) would mean the range line would vanish. In python 3 range is already a generator. 21.1.2 Plain cython First we’re going to need expressions – list/set/dict comprehensions – Literal dict and set expressions – yield expressions – Generator expressions – Boolean expressions consisting of only scalar values • Statements – Neither simple

axis=1) Out[127]: col1 0 1 1 2 2 3 Finally, one can also set a seed for sample’s random number generator using the random_state argument, which will 432 Chapter 2. User Guide pandas: powerful Python expressions – list/set/dict comprehensions – Literal dict and set expressions – yield expressions – Generator expressions – Boolean expressions consisting of only scalar values • Statements – Neither simple HDFStore.walk HDFStore.walk(where='/') Walk the pytables group hierarchy for pandas objects. This generator will yield the group path, subgroups and pandas object names for each group. Any non-pandas PyTables

axis=1) Out[127]: col1 0 1 1 2 2 3 Finally, one can also set a seed for sample’s random number generator using the random_state argument, which will accept either an integer (as a seed) or a NumPy RandomState expressions – list/set/dict comprehensions – Literal dict and set expressions – yield expressions – Generator expressions – Boolean expressions consisting of only scalar values • Statements – Neither simple HDFStore.walk HDFStore.walk(where='/') Walk the pytables group hierarchy for pandas objects. This generator will yield the group path, subgroups and pandas object names for each group. Any non-pandas PyTables

axis=1) Out[127]: col1 0 1 1 2 2 3 Finally, one can also set a seed for sample’s random number generator using the random_state argument, which will accept either an integer (as a seed) or a NumPy RandomState Guides 957 pandas: powerful Python data analysis toolkit, Release 1.5.0rc0 – yield expressions – Generator expressions – Boolean expressions consisting of only scalar values • Statements – Neither simple formatted cells into Excel an excel sheet Deprecated since version 1.5.0. Parameters cells [generator] cell of formatted data to save to Excel sheet sheet_name [str, default None] Name of Excel sheet

between_time can now select times across midnight (GH1871) • Series constructor can now handle generator as input (GH1679) • DataFrame.dropna can now take multiple axes (tuple/list) as input (GH924) Note: In python 2 replacing the range with its generator counterpart (xrange) would mean the range line would vanish. In python 3 range is already a generator. 21.1.2 Plain cython First we’re going to need expressions – list/set/dict comprehensions – Literal dict and set expressions – yield expressions – Generator expressions – Boolean expressions consisting of only scalar values • Statements – Neither simple

pandas: powerful Python data analysis toolkit, Release 0.19.0 • Series constructor can now handle generator as input (GH1679) • DataFrame.dropna can now take multiple axes (tuple/list) as input (GH924) analysis toolkit, Release 0.19.0 2 3 Finally, one can also set a seed for sample‘s random number generator using the random_state argument, which will accept either an integer (as a seed) or a numpy RandomState Note: In python 2 replacing the range with its generator counterpart (xrange) would mean the range line would vanish. In python 3 range is already a generator. Plain cython First we’re going to need to

pandas: powerful Python data analysis toolkit, Release 0.19.1 • Series constructor can now handle generator as input (GH1679) • DataFrame.dropna can now take multiple axes (tuple/list) as input (GH924) analysis toolkit, Release 0.19.1 2 3 Finally, one can also set a seed for sample‘s random number generator using the random_state argument, which will accept either an integer (as a seed) or a numpy RandomState Note: In python 2 replacing the range with its generator counterpart (xrange) would mean the range line would vanish. In python 3 range is already a generator. Plain cython First we’re going to need to

between_time can now select times across midnight (GH1871) • Series constructor can now handle generator as input (GH1679) • DataFrame.dropna can now take multiple axes (tuple/list) as input (GH924) axis=1) Out[113]: col1 0 1 1 2 2 3 Finally, one can also set a seed for sample‘s random number generator using the random_state argument, which will accept either an integer (as a seed) or a numpy RandomState Note: In python 2 replacing the range with its generator counterpart (xrange) would mean the range line would vanish. In python 3 range is already a generator. 26.1.2 Plain cython First we’re going to need