Price of Storage¶
Graph of the price of storage over time; data taken from http://www.mkomo.com/cost-per-gigabyte-update
In [1]:
import pandas as pd
data = '../data/memory-price.csv'
pd.read_csv(data).head()
Out[1]:
| Unnamed: 0 | date | driveInfo | sizeInMb | cost | dollarsPerGb | |
|---|---|---|---|---|---|---|
| 0 | 0 | 1980 January | Morrow Designs | 26.0 | 5000.0 | 193000.0 |
| 1 | 1 | 1980 July | North Star | 18.0 | 4199.0 | 233000.0 |
| 2 | 2 | 1981 September | Apple | 5.0 | 3500.0 | 700000.0 |
| 3 | 3 | 1981 November | Seagate | 5.0 | 1700.0 | 340000.0 |
| 4 | 4 | 1981 December | VR Data Corp. | 6.3 | 2895.0 | 460000.0 |
In [2]:
from altair import *
DriveSize = Formula(field='DriveSize',
expr=('{x}<1E3?"MB":{x}<1E6?"GB":"TB"'
''.format(x='datum.sizeInMb')))
Chart(data).mark_circle().encode(
x=X('date:T', timeUnit='year', axis=Axis(title=' ')),
y=Y('dollarsPerGb:Q', scale=Scale(type='log'),
axis=Axis(grid=False, format='$', title='Cost per GB')),
color=Color('DriveSize:N',
scale=Scale(domain=['MB', 'GB', 'TB']))
).transform_data(
calculate=[DriveSize]
)
