Example usage

Here we will demonstrate how to use pystockwatch in a project to calculate profit percent and volume change of stocks and plot the results.

import pystockwatch

print(pystockwatch.__version__)

0.3.4

Imports

from pystockwatch.pystockwatch import percent_change
from pystockwatch.pystockwatch import profit_viz
from pystockwatch.pystockwatch import volume_change
from pystockwatch.pystockwatch import volume_viz
import altair as alt
alt.renderers.enable('html')

RendererRegistry.enable('html')

To check the Profit percent of the stock

We ll use the percent_change() function created to calculate the profit percent of the stock ticker for the date range given below

percent_change('AAPL', '2017-01-01', '2019-01-10')

[*********************100%***********************]  1 of 1 completed

	Price Change Percentage(%)
Date
2017-01-03	0.000
2017-01-04	-0.112
2017-01-05	0.396
2017-01-06	1.515
2017-01-09	2.445
...	...
2019-01-03	22.419
2019-01-04	27.645
2019-01-07	27.361
2019-01-08	29.789
2019-01-09	31.993

508 rows × 1 columns

To Visualize the profit percentage change trend of a stock against market benchmark

We ll now plot the change in the profit percent of the stock ticker for the date range given below and compare it against the benchmark ticker

profit_viz('AAPL', '2017-01-01', '2019-01-10', 'MSFT')

[*********************100%***********************]  1 of 1 completed

[*********************100%***********************]  1 of 1 completed

To check daily trading volume change of a stock

We can calculate the daily trading volume change of a stock , whether it increases or decreases compared to the previous day using volume_change function below:

volume_change('AAPL', '2017-01-01', '2019-01-10')

	Date	Volume	Price_change
0	2017-01-03	115127600.0	nan
1	2017-01-04	84472400.0	Decrease
2	2017-01-05	88774400.0	Increase
3	2017-01-06	127007600.0	Increase
4	2017-01-09	134247600.0	Increase
...	...	...	...
504	2019-01-04	234428400.0	Increase
505	2019-01-07	219111200.0	Decrease
506	2019-01-08	164101200.0	Increase
507	2019-01-09	180396400.0	Increase
508	2019-01-10	143122800.0	Increase

509 rows × 3 columns

To Visualize the volume change trend of a stock

To plot the change in the daily change in volume of the stock ticker for the date range we use the volume_viz function

vol = volume_viz('AAPL', '2017-01-01', '2019-01-10')
vol.show()