Charting Data with PyKX¶

This workbook details example of interfacing PyKX with Python charting libraries.

PyKX supports rich datatype mapping meaning you can convert data from PyKX objects to:

• Python objects using .py()
• NumPy objects using .np()
• Pandas objects using .pd()
• PyArrow objects using .pa()

The full breakdown of how these map is documented here.

These resulting objects will behave as expected with all Python libraries.

For efficiency and exactness the examples below aim to use PyKX objects directly, minimising conversions when possible.

In [2]:

import pykx as kx
tab = kx.Table(data={
    'sym':kx.random.random(1000, ['a', 'b', 'c']), 
    'price':kx.random.random(1000, 1.0), 
    'size':kx.random.random(1000, 10),
    'quantity':kx.random.random(1000,100),
    'in_stock':kx.random.random(1000, [True, False])})
tab.head()

import pykx as kx tab = kx.Table(data={ 'sym':kx.random.random(1000, ['a', 'b', 'c']), 'price':kx.random.random(1000, 1.0), 'size':kx.random.random(1000, 10), 'quantity':kx.random.random(1000,100), 'in_stock':kx.random.random(1000, [True, False])}) tab.head()

Out[2]:

	sym	price	size	quantity	in_stock
0	a	0.9094126	4	5	1b
1	a	0.2988477	5	18	1b
2	c	0.454063	8	11	0b
3	b	0.156942	1	36	1b
4	c	0.04699265	4	43	1b

Matplotlib¶

Generating a scatter plot using the price and size columns of our table.

The scatter(tab['price'], tab['quantity']) notation is used to access PyKX objects directly.

To use x= and y= syntax requires conversion to a dataframe using .pd() .i.e scatter(tab.pd(), x='price' ,y='quantity')

scatter fundamentally uses a series of 1D arrays and is therefore one of the only charts where the column values do not need to first be converted in Numpy objects using .np().

In [3]:

import matplotlib.pyplot as plt

plt.scatter(tab['price'], tab['quantity'])
plt.show()

import matplotlib.pyplot as plt plt.scatter(tab['price'], tab['quantity']) plt.show()

In order for the column values to be compatible with most of matplotlib charts, they first must be converted to numpy objects using the .np() function.

In [4]:

plt.bar(tab['size'].np(), tab['price'].np())
plt.show()

plt.bar(tab['size'].np(), tab['price'].np()) plt.show()

Plotly¶

Plotly allows vector objects to be passed as the color argument. This parameter is set using the sym column resulting in the scatter chart below.

In [5]:

import plotly.express as px

fig = px.scatter(
    x=tab['quantity'],
    y=tab['price'],
    size=tab['size'],
    color=tab['sym'])
fig.show(renderer="png")

import plotly.express as px fig = px.scatter( x=tab['quantity'], y=tab['price'], size=tab['size'], color=tab['sym']) fig.show(renderer="png")