In [1]:
import altair as alt
#alt.enable_mime_rendering()
# load built-in dataset as a pandas DataFrame
cars = alt.load_dataset('cars')
# Uncomment for rendering in JupyterLab & nteract
# alt.enable_mime_rendering()
alt.Chart(cars).mark_circle().encode(
x='Horsepower',
y='Miles_per_Gallon',
color='Origin',
).display()
In [2]:
from vega_datasets import data
In [9]:
source = data.seattle_temps()
source
Out[9]:
date
temp
0
2010-01-01 00:00:00
39.4
1
2010-01-01 01:00:00
39.2
2
2010-01-01 02:00:00
39.0
3
2010-01-01 03:00:00
38.9
4
2010-01-01 04:00:00
38.8
5
2010-01-01 05:00:00
38.7
6
2010-01-01 06:00:00
38.7
7
2010-01-01 07:00:00
38.6
8
2010-01-01 08:00:00
38.7
9
2010-01-01 09:00:00
39.2
10
2010-01-01 10:00:00
40.1
11
2010-01-01 11:00:00
41.3
12
2010-01-01 12:00:00
42.5
13
2010-01-01 13:00:00
43.2
14
2010-01-01 14:00:00
43.5
15
2010-01-01 15:00:00
43.3
16
2010-01-01 16:00:00
42.7
17
2010-01-01 17:00:00
41.7
18
2010-01-01 18:00:00
41.2
19
2010-01-01 19:00:00
40.9
20
2010-01-01 20:00:00
40.7
21
2010-01-01 21:00:00
40.4
22
2010-01-01 22:00:00
40.2
23
2010-01-01 23:00:00
39.9
24
2010-01-02 00:00:00
39.6
25
2010-01-02 01:00:00
39.4
26
2010-01-02 02:00:00
39.3
27
2010-01-02 03:00:00
39.1
28
2010-01-02 04:00:00
39.0
29
2010-01-02 05:00:00
38.9
...
...
...
8729
2010-12-30 18:00:00
40.8
8730
2010-12-30 19:00:00
40.5
8731
2010-12-30 20:00:00
40.3
8732
2010-12-30 21:00:00
40.0
8733
2010-12-30 22:00:00
39.8
8734
2010-12-30 23:00:00
39.5
8735
2010-12-31 00:00:00
39.2
8736
2010-12-31 01:00:00
39.0
8737
2010-12-31 02:00:00
38.9
8738
2010-12-31 03:00:00
38.7
8739
2010-12-31 04:00:00
38.6
8740
2010-12-31 05:00:00
38.5
8741
2010-12-31 06:00:00
38.5
8742
2010-12-31 07:00:00
38.4
8743
2010-12-31 08:00:00
38.5
8744
2010-12-31 09:00:00
39.0
8745
2010-12-31 10:00:00
40.0
8746
2010-12-31 11:00:00
41.2
8747
2010-12-31 12:00:00
42.3
8748
2010-12-31 13:00:00
43.0
8749
2010-12-31 14:00:00
43.3
8750
2010-12-31 15:00:00
43.1
8751
2010-12-31 16:00:00
42.5
8752
2010-12-31 17:00:00
41.5
8753
2010-12-31 18:00:00
41.0
8754
2010-12-31 19:00:00
40.7
8755
2010-12-31 20:00:00
40.5
8756
2010-12-31 21:00:00
40.2
8757
2010-12-31 22:00:00
40.0
8758
2010-12-31 23:00:00
39.6
8759 rows × 2 columns
In [23]:
chart = alt.Chart(source, max_rows=10000).mark_area().encode(
x=alt.X('date:T', timeUnit='month', axis=alt.Axis(title='Month of the year')),
y='temp',
row = alt.Row('date:T', timeUnit='hours')
).display()
In [11]:
chart
---------------------------------------------------------------------------
MaxRowsExceeded Traceback (most recent call last)
/home/saket/anaconda2/lib/python2.7/site-packages/IPython/core/formatters.pyc in __call__(self, obj)
913 method = get_real_method(obj, self.print_method)
914 if method is not None:
--> 915 method()
916 return True
917
/home/saket/anaconda2/lib/python2.7/site-packages/altair/v1/api.pyc in _ipython_display_(self)
443 from IPython.display import display
444 from vega import VegaLite
--> 445 display(VegaLite(self.to_dict(validate_columns=True)))
446
447 def display(self):
/home/saket/anaconda2/lib/python2.7/site-packages/altair/v1/api.pyc in to_dict(self, data, validate_columns)
287 The JSON specification of the chart object.
288 """
--> 289 dct = super(TopLevelMixin, self.clone()).to_dict(data=data, validate_columns=validate_columns)
290 dct['$schema'] = schema.vegalite_schema_url
291 return dct
/home/saket/anaconda2/lib/python2.7/site-packages/altair/v1/schema/_interface/jstraitlets.pyc in to_dict(self, **kwargs)
151 def to_dict(self, **kwargs):
152 """Output a (nested) dict encoding the contents of this instance"""
--> 153 self._finalize(**kwargs)
154 Visitor = self._converter_registry.get('to_dict', ToDict)
155 return Visitor().visit(self, **kwargs)
/home/saket/anaconda2/lib/python2.7/site-packages/altair/v1/api.pyc in _finalize(self, **kwargs)
491
492 def _finalize(self, **kwargs):
--> 493 self._finalize_data()
494 # data comes from wrappers, but self.data overrides this if defined
495 if self.data is not None:
/home/saket/anaconda2/lib/python2.7/site-packages/altair/v1/api.pyc in _finalize_data(self)
546 "your Chart to an integer larger than the number of rows "
547 "in your dataset. Alternatively you could perform aggregations "
--> 548 "or other data reductions before using it with Altair" % DEFAULT_MAX_ROWS
549 )
550
MaxRowsExceeded: Your dataset has too many rows and could take a long time to send to the frontend or to render. To override the default maximum rows (5000), set the max_rows property of your Chart to an integer larger than the number of rows in your dataset. Alternatively you could perform aggregations or other data reductions before using it with Altair
<traitlets.traitlets.Chart at 0x7f6f17124d90>
In [ ]:
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