def test_chart_infer_types():
data = pd.DataFrame({'x': pd.date_range('2012', periods=10, freq='Y'),
'y': range(10),
'c': list('abcabcabca')})
def _check_encodings(chart):
dct = chart.to_dict()
assert dct['encoding']['x']['type'] == 'temporal'
assert dct['encoding']['x']['field'] == 'x'
assert dct['encoding']['y']['type'] == 'quantitative'
assert dct['encoding']['y']['field'] == 'y'
assert dct['encoding']['color']['type'] == 'nominal'
assert dct['encoding']['color']['field'] == 'c'
# Pass field names by keyword
chart = alt.Chart(data).mark_point().encode(x='x', y='y', color='c')
_check_encodings(chart)
# pass Channel objects by keyword
chart = alt.Chart(data).mark_point().encode(x=alt.X('x'), y=alt.Y('y'),
color=alt.Color('c'))
_check_encodings(chart)
# pass Channel objects by value
chart = alt.Chart(data).mark_point().encode(alt.X('x'), alt.Y('y'),
alt.Color('c'))
_check_encodings(chart)
# override default types
chart = alt.Chart(data).mark_point().encode(alt.X('x', type='nominal'),
alt.Y('y', type='ordinal'))
dct = chart.to_dict()
assert dct['encoding']['x']['type'] == 'nominal'
assert dct['encoding']['y']['type'] == 'ordinal'
def make_bump_chart(self):
self.plot_df['year'] = pd.to_datetime(
self.plot_df['year'].astype(str) + '-01-01')
brush = alt.selection(type='interval', encodings=['x'])
a = alt.Chart(self.plot_df).mark_line(
point=True, interpolate='monotone').encode(
x='year:T',
y='rank:Q',
color=alt.Color('Topic:N', sort='descending'),
tooltip=['year:T', 'rank:Q', 'Topic:N', 'rate']).properties(
height=400,
width=800).transform_filter(brush).interactive()
b = alt.Chart(self.plot_df).mark_area().encode(
y='sum(rate):Q',
x='year:T',
).properties(width=800, height=100).add_selection(brush)
if self.add_data_names != ['All']:
add_charts = [
self.make_add_data_chart(i, brush) for i in self.add_data_names
]
chart = alt.vconcat(a, *add_charts, b, padding=0,
spacing=0).configure_view(
stroke=None).configure_axis(grid=False)
return chart
else:
chart = alt.vconcat(a, b, padding=0, spacing=0).configure_view(
stroke=None).configure_axis(grid=False)
return chart
def make_ridge_chart(self):
self.plot_df['year'] = pd.to_datetime(
self.plot_df['year'].astype(str) + '-01-01')
brush = alt.selection_interval(encodings=['x'])
step = 18
overlap = 7
# Topic selection
selection = alt.selection_multi(fields=['Topic'])
# смена цвета на выборе темы -- всё что не выделили делается серым
color = alt.condition(
selection,
alt.Color('Topic:N',
legend=None,
scale=alt.Scale(scheme="rainbow")),
alt.value('lightgray'))
a = alt.hconcat(
alt.Chart(self.plot_df).mark_area(
fillOpacity=0.6, interpolate='monotone').encode(
x=alt.X('year:T'),
y=alt.Y('rate:Q',
scale=alt.Scale(range=[0, -overlap * (step + 1)]),
axis=None),
row=alt.Row('Topic:N',
header=alt.Header(title=None,
labelPadding=0,
labelFontSize=0)),
color=color).add_selection(selection).properties(
width=800,
height=step,
bounds='flush',
).transform_filter(brush),
alt.Chart(self.plot_df,
height=500).mark_point().encode(
y=alt.Y('Topic:N', axis=alt.Axis(orient='right')),
color=color).add_selection(selection))
b = alt.Chart(self.plot_df).mark_area(interpolate='monotone').encode(
y='sum(rate):Q',
x='year:T',
).properties(width=800, height=100).add_selection(brush)
if self.add_data_names != ['All']:
add_charts = [
self.make_add_data_chart(i, brush) for i in self.add_data_names
]
chart = alt.vconcat(a, *add_charts, b, padding=0,
spacing=0).configure_view(
stroke=None).configure_axis(grid=False)
return chart
else:
chart = alt.vconcat(a, b, padding=0, spacing=0).configure_view(
stroke=None).configure_axis(grid=False)
return chart
def test_chart_infer_types():
data = pd.DataFrame({
"x": pd.date_range("2012", periods=10, freq="Y"),
"y": range(10),
"c": list("abcabcabca"),
})
def _check_encodings(chart):
dct = chart.to_dict()
assert dct["encoding"]["x"]["type"] == "temporal"
assert dct["encoding"]["x"]["field"] == "x"
assert dct["encoding"]["y"]["type"] == "quantitative"
assert dct["encoding"]["y"]["field"] == "y"
assert dct["encoding"]["color"]["type"] == "nominal"
assert dct["encoding"]["color"]["field"] == "c"
# Pass field names by keyword
chart = alt.Chart(data).mark_point().encode(x="x", y="y", color="c")
_check_encodings(chart)
# pass Channel objects by keyword
chart = (alt.Chart(data).mark_point().encode(x=alt.X("x"),
y=alt.Y("y"),
color=alt.Color("c")))
_check_encodings(chart)
# pass Channel objects by value
chart = alt.Chart(data).mark_point().encode(alt.X("x"), alt.Y("y"),
alt.Color("c"))
_check_encodings(chart)
# override default types
chart = (alt.Chart(data).mark_point().encode(alt.X("x", type="nominal"),
alt.Y("y", type="ordinal")))
dct = chart.to_dict()
assert dct["encoding"]["x"]["type"] == "nominal"
assert dct["encoding"]["y"]["type"] == "ordinal"
def test_selection_to_dict():
brush = alt.selection(type='interval')
# test some value selections
# Note: X and Y cannot have conditions
alt.Chart('path/to/data.json').mark_point().encode(
color=alt.condition(brush, alt.ColorValue('red'),
alt.ColorValue('blue')),
opacity=alt.condition(brush, alt.value(0.5), alt.value(1.0)),
text=alt.condition(brush, alt.TextValue('foo'),
alt.value('bar'))).to_dict()
# test some field selections
# Note: X and Y cannot have conditions
# Conditions cannot both be fields
alt.Chart('path/to/data.json').mark_point().encode(
color=alt.condition(brush, alt.Color('col1:N'), alt.value('blue')),
opacity=alt.condition(brush, 'col1:N', alt.value(0.5)),
text=alt.condition(brush, alt.value('abc'), alt.Text('col2:N')),
size=alt.condition(brush, alt.value(20), 'col2:N')).to_dict()
def test_selection_to_dict():
brush = alt.selection(type="interval")
# test some value selections
# Note: X and Y cannot have conditions
alt.Chart("path/to/data.json").mark_point().encode(
color=alt.condition(brush, alt.ColorValue("red"),
alt.ColorValue("blue")),
opacity=alt.condition(brush, alt.value(0.5), alt.value(1.0)),
text=alt.condition(brush, alt.TextValue("foo"), alt.value("bar")),
).to_dict()
# test some field selections
# Note: X and Y cannot have conditions
# Conditions cannot both be fields
alt.Chart("path/to/data.json").mark_point().encode(
color=alt.condition(brush, alt.Color("col1:N"), alt.value("blue")),
opacity=alt.condition(brush, "col1:N", alt.value(0.5)),
text=alt.condition(brush, alt.value("abc"), alt.Text("col2:N")),
size=alt.condition(brush, alt.value(20), "col2:N"),
).to_dict()
