arkouda.plotting

Module Contents

Functions

hist_all(ak_df[, cols])	Create a grid plot histogramming all numeric columns in ak dataframe
plot_dist(b, h[, log, xlabel, newfig])	Plot the distribution and cumulative distribution of histogram Data

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

Create a grid plot histogramming all numeric columns in ak dataframe

Parameters:

• ak_df (ak.DataFrame) – Full Arkouda DataFrame containing data to be visualized

• cols (list) – (Optional) A specified list of columns to be plotted

Notes

This function displays the plot.

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)

arkouda.plotting.plot_dist(b, h, log=True, xlabel=None, newfig=True)

Plot the distribution and cumulative distribution of histogram Data

Parameters:

• b (np.ndarray) – Bin edges

• h (np.ndarray) – Histogram data

• log (bool) – use log to scale y

• xlabel (str) – Label for the x axis of the graph

• newfig (bool) – Generate a new figure or not

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.

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()