In [1]:
%matplotlib inline
import matplotlib.pyplot as plt
plt.style.use('seaborn')
In [2]:
from jupyterworkflow.data import get_fremont_data
In [3]:
data = get_fremont_data()
data.head()
Out[3]:
| West | East | Total | |
|---|---|---|---|
| Date | |||
| 2012-10-03 00:00:00 | 4.0 | 9.0 | 13.0 |
| 2012-10-03 01:00:00 | 4.0 | 6.0 | 10.0 |
| 2012-10-03 02:00:00 | 1.0 | 1.0 | 2.0 |
| 2012-10-03 03:00:00 | 2.0 | 3.0 | 5.0 |
| 2012-10-03 04:00:00 | 6.0 | 1.0 | 7.0 |
In [4]:
data.resample('W').sum().plot();
In [5]:
data.groupby(data.index.time).mean().plot();
In [6]:
pivoted = data.pivot_table('Total', index=data.index.time, columns=data.index.date)
pivoted.iloc[:5, :5]
Out[6]:
| 2012-10-03 | 2012-10-04 | 2012-10-05 | 2012-10-06 | 2012-10-07 | |
|---|---|---|---|---|---|
| 00:00:00 | 13.0 | 18.0 | 11.0 | 15.0 | 11.0 |
| 01:00:00 | 10.0 | 3.0 | 8.0 | 15.0 | 17.0 |
| 02:00:00 | 2.0 | 9.0 | 7.0 | 9.0 | 3.0 |
| 03:00:00 | 5.0 | 3.0 | 4.0 | 3.0 | 6.0 |
| 04:00:00 | 7.0 | 8.0 | 9.0 | 5.0 | 3.0 |
In [7]:
pivoted.plot(legend=False, alpha=0.01);
In [ ]: