from datascience import *
import numpy as np
import seaborn as sns
Table.interactive_plots()
tips = Table.from_df(sns.load_dataset('tips'))
tips
total_bill | tip | sex | smoker | day | time | size |
---|---|---|---|---|---|---|
16.99 | 1.01 | Female | No | Sun | Dinner | 2 |
10.34 | 1.66 | Male | No | Sun | Dinner | 3 |
21.01 | 3.5 | Male | No | Sun | Dinner | 3 |
23.68 | 3.31 | Male | No | Sun | Dinner | 2 |
24.59 | 3.61 | Female | No | Sun | Dinner | 4 |
25.29 | 4.71 | Male | No | Sun | Dinner | 4 |
8.77 | 2 | Male | No | Sun | Dinner | 2 |
26.88 | 3.12 | Male | No | Sun | Dinner | 4 |
15.04 | 1.96 | Male | No | Sun | Dinner | 2 |
14.78 | 3.23 | Male | No | Sun | Dinner | 2 |
... (234 rows omitted)
tips.group('time').barh('time')