arkouda.plotting
================

.. py:module:: arkouda.plotting


Functions
---------

.. autoapisummary::

   arkouda.plotting.hist_all
   arkouda.plotting.plot_dist


Module Contents
---------------

.. py:function:: hist_all(ak_df: arkouda.dataframe.DataFrame, cols: list = [])

   Create a grid plot histogramming all numeric columns in ak dataframe

   :param ak_df: Full Arkouda DataFrame containing data to be visualized
   :type ak_df: ak.DataFrame
   :param cols: (Optional) A specified list of columns to be plotted
   :type cols: list

   .. rubric:: Notes

   This function displays the plot.

   .. rubric:: Examples

   >>> import arkouda as ak
   >>> from arkouda.plotting import hist_all
   >>> ak_df = ak.DataFrame({"a": ak.array(np.random.randn(100)),
                             "b": ak.array(np.random.randn(100)),
                             "c": ak.array(np.random.randn(100)),
                             "d": ak.array(np.random.randn(100))
                             })
   >>> hist_all(ak_df)


.. py:function:: plot_dist(b, h, log=True, xlabel=None, newfig=True)

   Plot the distribution and cumulative distribution of histogram Data

   :param b: Bin edges
   :type b: np.ndarray
   :param h: Histogram data
   :type h: np.ndarray
   :param log: use log to scale y
   :type log: bool
   :param xlabel: Label for the x axis of the graph
   :type xlabel: str
   :param newfig: Generate a new figure or not
   :type newfig: bool

   .. rubric:: Notes

   This function does not return or display the plot. A user must have matplotlib imported in
   addition to arkouda to display plots. This could be updated to return the object or have a
   flag to show the resulting plots.
   See Examples Below.

   .. rubric:: Examples

   >>> import arkouda as ak
   >>> from matplotlib import pyplot as plt
   >>> b, h = ak.histogram(ak.arange(10), 3)
   >>> ak.plot_dist(b, h.to_ndarray())
   >>> # to show the plot
   >>> plt.show()