def encode_color(self):
AltairChart.encode_color(self)
self.add_text()
# Setting tooltip as non-null
self.chart = self.chart.configure_mark(
tooltip=alt.TooltipContent("encoding"))
self.code += f"""chart = chart.configure_mark(tooltip=alt.TooltipContent('encoding'))"""
def encode_color(
self
): # override encode_color in AltairChart to enforce add_text occurs afterwards
AltairChart.encode_color(self)
self.add_text()
self.chart = self.chart.configure_mark(tooltip=alt.TooltipContent(
'encoding')) # Setting tooltip as non-null
self.code += f'''chart = chart.configure_mark(tooltip=alt.TooltipContent('encoding'))'''
def initialize_chart(self):
x_attr = self.vis.get_attr_by_channel("x")[0]
y_attr = self.vis.get_attr_by_channel("y")[0]
x_attr_abv = str(x_attr.attribute)
y_attr_abv = str(y_attr.attribute)
background, background_str = self.get_background(x_attr_abv.lower())
geographical_name = self.get_geographical_name(x_attr_abv.lower())
geo_map, geo_map_str, map_type, map_translation = self.get_geomap(
x_attr_abv.lower())
self.data[x_attr_abv] = self.data[x_attr_abv].apply(map_translation)
if len(x_attr_abv) > 25:
x_attr_abv = x_attr.attribute[:15] + "..." + x_attr.attribute[-10:]
if len(y_attr_abv) > 25:
y_attr_abv = y_attr.attribute[:15] + "..." + y_attr.attribute[-10:]
if isinstance(x_attr.attribute, str):
x_attr.attribute = x_attr.attribute.replace(".", "")
if isinstance(y_attr.attribute, str):
y_attr.attribute = y_attr.attribute.replace(".", "")
self.data = AltairChart.sanitize_dataframe(self.data)
points = (alt.Chart(geo_map).mark_geoshape().encode(
color=f"{str(y_attr.attribute)}:Q", ).transform_lookup(
lookup="id",
from_=alt.LookupData(self.data, str(x_attr.attribute),
[str(y_attr.attribute)]),
).project(type=map_type).properties(
title=f"Mean of {y_attr_abv} across {geographical_name}"))
chart = background + points
######################################
## Constructing Altair Code String ##
#####################################
self.code += "import altair as alt\n"
dfname = "placeholder_variable"
self.code += f"""nan=float('nan')
df = pd.DataFrame({str(self.data.to_dict())})
background = {background_str}
points = alt.Chart({geo_map_str}).mark_geoshape().encode(
color='{str(y_attr.attribute)}:Q',
).transform_lookup(
lookup='id',
from_=alt.LookupData({dfname}, "{str(x_attr.attribute)}", ["{str(y_attr.attribute)}"])
).project(
type="{map_type}"
).properties(
title="Mean of {y_attr_abv} across {geographical_name}"
)
chart = background + points
"""
return chart
def initialize_chart(self):
x_attr = self.vis.get_attr_by_channel("x")[0]
y_attr = self.vis.get_attr_by_channel("y")[0]
x_attr_abv = str(x_attr.attribute)
y_attr_abv = str(y_attr.attribute)
if len(x_attr_abv) > 25:
x_attr_abv = x_attr.attribute[:15] + "..." + x_attr.attribute[-10:]
if len(y_attr_abv) > 25:
y_attr_abv = y_attr.attribute[:15] + "..." + y_attr.attribute[-10:]
x_min = self.vis.min_max[x_attr.attribute][0]
x_max = self.vis.min_max[x_attr.attribute][1]
y_min = self.vis.min_max[y_attr.attribute][0]
y_max = self.vis.min_max[y_attr.attribute][1]
if isinstance(x_attr.attribute, str):
x_attr.attribute = x_attr.attribute.replace(".", "")
if isinstance(y_attr.attribute, str):
y_attr.attribute = y_attr.attribute.replace(".", "")
self.data = AltairChart.sanitize_dataframe(self.data)
chart = (alt.Chart(self.data).mark_circle().encode(
x=alt.X(
str(x_attr.attribute),
scale=alt.Scale(domain=(x_min, x_max)),
type=x_attr.data_type,
axis=alt.Axis(title=x_attr_abv),
),
y=alt.Y(
str(y_attr.attribute),
scale=alt.Scale(domain=(y_min, y_max)),
type=y_attr.data_type,
axis=alt.Axis(title=y_attr_abv),
),
))
# Setting tooltip as non-null
chart = chart.configure_mark(tooltip=alt.TooltipContent("encoding"))
chart = chart.interactive() # Enable Zooming and Panning
#####################################
## Constructing Altair Code String ##
#####################################
self.code += "import altair as alt\n"
dfname = "placeholder_variable"
self.code += f"""
chart = alt.Chart({dfname}).mark_circle().encode(
x=alt.X('{x_attr.attribute}',scale=alt.Scale(domain=({x_min}, {x_max})),type='{x_attr.data_type}', axis=alt.Axis(title='{x_attr_abv}')),
y=alt.Y('{y_attr.attribute}',scale=alt.Scale(domain=({y_min}, {y_max})),type='{y_attr.data_type}', axis=alt.Axis(title='{y_attr_abv}'))
)
chart = chart.configure_mark(tooltip=alt.TooltipContent('encoding')) # Setting tooltip as non-null
chart = chart.interactive() # Enable Zooming and Panning
"""
return chart
def initialize_chart(self):
self.tooltip = False
x_attr = self.vis.get_attr_by_channel("x")[0]
y_attr = self.vis.get_attr_by_channel("y")[0]
x_attr_abv = str(x_attr.attribute)
y_attr_abv = str(y_attr.attribute)
if len(x_attr_abv) > 25:
x_attr_abv = x_attr.attribute[:15] + "..." + x_attr.attribute[-10:]
if len(y_attr_abv) > 25:
y_attr_abv = y_attr.attribute[:15] + "..." + y_attr.attribute[-10:]
if isinstance(x_attr.attribute, str):
x_attr.attribute = x_attr.attribute.replace(".", "")
if isinstance(y_attr.attribute, str):
y_attr.attribute = y_attr.attribute.replace(".", "")
# To get datetime to display correctly on bar charts
if x_attr.data_type == "temporal":
x_attr.data_type = "nominal"
self.code += "from pandas import Timestamp\n"
if y_attr.data_type == "temporal":
y_attr.data_type = "nominal"
self.code += "from pandas import Timestamp\n"
if x_attr.data_model == "measure":
agg_title = get_agg_title(x_attr)
measure_attr = x_attr.attribute
y_attr_field = alt.Y(
str(y_attr.attribute),
type=y_attr.data_type,
axis=alt.Axis(labelOverlap=True, title=y_attr_abv),
)
x_attr_field = alt.X(
str(x_attr.attribute),
type=x_attr.data_type,
title=agg_title,
axis=alt.Axis(title=agg_title),
)
y_attr_field_code = f"alt.Y('{y_attr.attribute}', type= '{y_attr.data_type}', axis=alt.Axis(labelOverlap=True, title='{y_attr_abv}'))"
x_attr_field_code = f"alt.X('{x_attr.attribute}', type= '{x_attr.data_type}', title='{agg_title}', axis=alt.Axis(title='{agg_title}'))"
if y_attr.sort == "ascending":
y_attr_field.sort = "-x"
y_attr_field_code = f"alt.Y('{y_attr.attribute}', type= '{y_attr.data_type}', axis=alt.Axis(labelOverlap=True, title='{y_attr_abv}'), sort ='-x')"
else:
agg_title = get_agg_title(y_attr)
measure_attr = y_attr.attribute
x_attr_field = alt.X(
str(x_attr.attribute),
type=x_attr.data_type,
axis=alt.Axis(labelOverlap=True, title=x_attr_abv),
)
x_attr_field_code = f"alt.X('{x_attr.attribute}', type= '{x_attr.data_type}', axis=alt.Axis(labelOverlap=True, title='{x_attr_abv}'))"
y_attr_field = alt.Y(
str(y_attr.attribute),
type=y_attr.data_type,
title=agg_title,
axis=alt.Axis(title=agg_title),
)
y_attr_field_code = f"alt.Y('{y_attr.attribute}', type= '{y_attr.data_type}', title='{agg_title}', axis=alt.Axis(title='{agg_title}'))"
if x_attr.sort == "ascending":
x_attr_field.sort = "-y"
x_attr_field_code = f"alt.X('{x_attr.attribute}', type= '{x_attr.data_type}', axis=alt.Axis(labelOverlap=True, title='{x_attr_abv}'),sort='-y')"
k = 10
self._topkcode = ""
n_bars = len(self.data.iloc[:, 0].unique())
plotting_scale = lux.config.plotting_scale
if n_bars > k: # Truncating to only top k
remaining_bars = n_bars - k
self.data = self.data.nlargest(k, columns=measure_attr)
self.data = AltairChart.sanitize_dataframe(self.data)
self.text = alt.Chart(self.data).mark_text(
x=155 * plotting_scale,
y=142 * plotting_scale,
align="right",
color="#ff8e04",
fontSize=11,
text=f"+ {remaining_bars} more ...",
)
self._topkcode = f"""text = alt.Chart(visData).mark_text(
x={155 * plotting_scale},
y={142 * plotting_scale},
align="right",
color = "#ff8e04",
fontSize = 11,
text=f"+ {remaining_bars} more ..."
)
chart = chart + text\n"""
self.data = AltairChart.sanitize_dataframe(self.data)
chart = alt.Chart(self.data).mark_bar().encode(y=y_attr_field,
x=x_attr_field)
# TODO: tooltip messes up the count() bar charts
# Can not do interactive whenever you have default count measure otherwise output strange error (Javascript Error: Cannot read property 'length' of undefined)
# chart = chart.interactive() # If you want to enable Zooming and Panning
self.code += "import altair as alt\n"
# self.code += f"visData = pd.DataFrame({str(self.data.to_dict(orient='records'))})\n"
self.code += f"visData = pd.DataFrame({str(self.data.to_dict())})\n"
self.code += f"""
chart = alt.Chart(visData).mark_bar().encode(
y = {y_attr_field_code},
x = {x_attr_field_code},
)\n"""
return chart
def initialize_chart(self):
self.tooltip = False
measure = self.vis.get_attr_by_data_model("measure",
exclude_record=True)[0]
msr_attr = self.vis.get_attr_by_channel(measure.channel)[0]
msr_attr_abv = str(msr_attr.attribute)
if len(msr_attr_abv) > 17:
msr_attr_abv = msr_attr_abv[:10] + "..." + msr_attr_abv[-7:]
x_min = self.vis.min_max[msr_attr.attribute][0]
x_max = self.vis.min_max[msr_attr.attribute][1]
if isinstance(msr_attr.attribute, str):
msr_attr.attribute = msr_attr.attribute.replace(".", "")
colval = self.vis.data[msr_attr.attribute]
x_range = abs(max(colval) - min(colval))
plot_range = abs(x_max - x_min)
markbar = x_range / plot_range * 12
self.data = AltairChart.sanitize_dataframe(self.data)
axis_title = f"{msr_attr_abv} (binned)"
if msr_attr.attribute == " ":
axis_title = "Series (binned)"
if measure.channel == "x":
chart = (alt.Chart(self.data).mark_bar(size=markbar).encode(
alt.X(
str(msr_attr.attribute),
title=axis_title,
bin=alt.Bin(binned=True),
type=msr_attr.data_type,
axis=alt.Axis(labelOverlap=True, title=axis_title),
scale=alt.Scale(domain=(x_min, x_max)),
),
alt.Y("Number of Records", type="quantitative"),
))
elif measure.channel == "y":
chart = (alt.Chart(self.data).mark_bar(size=markbar).encode(
x=alt.X("Number of Records", type="quantitative"),
y=alt.Y(
str(msr_attr.attribute),
title=axis_title,
bin=alt.Bin(binned=True),
axis=alt.Axis(labelOverlap=True, title=axis_title),
scale=alt.Scale(domain=(x_min, x_max)),
),
))
#####################################
## Constructing Altair Code String ##
#####################################
self.code += "import altair as alt\n"
# self.code += f"visData = pd.DataFrame({str(self.data.to_dict(orient='records'))})\n"
self.code += f"visData = pd.DataFrame({str(self.data.to_dict())})\n"
if measure.channel == "x":
self.code += f"""
chart = alt.Chart(visData).mark_bar(size={markbar}).encode(
alt.X('{msr_attr.attribute}', title='{axis_title}',bin=alt.Bin(binned=True), type='{msr_attr.data_type}', axis=alt.Axis(labelOverlap=True, title='{axis_title}'), scale=alt.Scale(domain=({x_min}, {x_max}))),
alt.Y("Number of Records", type="quantitative")
)
"""
elif measure.channel == "y":
self.code += f"""
chart = alt.Chart(visData).mark_bar(size={markbar}).encode(
alt.Y('{msr_attr.attribute}', title='{axis_title}',bin=alt.Bin(binned=True), type='{msr_attr.data_type}', axis=alt.Axis(labelOverlap=True, title='{axis_title}'), scale=alt.Scale(domain=({x_min}, {x_max}))),
alt.X("Number of Records", type="quantitative")
)
"""
return chart
def initialize_chart(self):
self.tooltip = False
measure = self.vis.get_attr_by_data_model("measure",
exclude_record=True)[0]
msr_attr = self.vis.get_attr_by_channel(measure.channel)[0]
msr_attr_abv = str(msr_attr.attribute)
if len(msr_attr_abv) > 17:
msr_attr_abv = msr_attr_abv[:10] + "..." + msr_attr_abv[-7:]
x_min, x_max = self.vis.min_max[msr_attr.attribute]
x_range = abs(x_max - x_min)
if isinstance(msr_attr.attribute, str):
msr_attr.attribute = msr_attr.attribute.replace(".", "")
markbar = compute_bin_width(self.data[msr_attr.attribute])
step = abs(self.data[msr_attr.attribute][1] -
self.data[msr_attr.attribute][0])
# Default when bin too small
if markbar < (x_range / 24):
markbar = (x_max - x_min) / 12
self.data = AltairChart.sanitize_dataframe(self.data)
end_attr_abv = str(msr_attr.attribute) + "_end"
self.data[end_attr_abv] = self.data[str(msr_attr.attribute)] + markbar
axis_title = f"{msr_attr_abv} (binned)"
if msr_attr.attribute == " ":
axis_title = "Series (binned)"
if measure.channel == "x":
chart = (alt.Chart(self.data).mark_bar().encode(
x=alt.X(
str(msr_attr.attribute),
title=axis_title,
bin=alt.Bin(binned=True, step=step),
type=msr_attr.data_type,
axis=alt.Axis(title=axis_title),
scale=alt.Scale(domain=[x_min, x_max]),
),
x2=end_attr_abv,
y=alt.Y("Number of Records", type="quantitative"),
))
elif measure.channel == "y":
chart = (alt.Chart(self.data).mark_bar().encode(
x=alt.X("Number of Records", type="quantitative"),
y=alt.Y(
str(msr_attr.attribute),
title=axis_title,
bin=alt.Bin(binned=True, step=step),
type=msr_attr.data_type,
axis=alt.Axis(title=axis_title),
),
y2=end_attr_abv,
))
#####################################
## Constructing Altair Code String ##
#####################################
self.code += "import altair as alt\n"
self.code += f"visData = pd.DataFrame({str(self.data.to_dict())})\n"
if measure.channel == "x":
self.code += f"""
chart = alt.Chart(visData).mark_bar().encode(
x=alt.X('{msr_attr.attribute}', title='{axis_title}',bin=alt.Bin(binned=True, step={step}), type='{msr_attr.data_type}', axis=alt.Axis(labelOverlap=True, title='{axis_title}'), scale=alt.Scale(domain=({x_min}, {x_max}))),
x2='{end_attr_abv}',
y=alt.Y("Number of Records", type="quantitative")
)
"""
elif measure.channel == "y":
self.code += f"""
chart = alt.Chart(visData).mark_bar().encode(
y=alt.Y('{msr_attr.attribute}', title='{axis_title}', bin=alt.Bin(binned=True, step={step}), type='{msr_attr.data_type}', axis=alt.Axis(labelOverlap=True, title='{axis_title}')),
y2='{end_attr_abv}',
x=alt.X("Number of Records", type="quantitative")
)
"""
return chart
def initialize_chart(self):
self.tooltip = False # tooltip looks weird for line chart
x_attr = self.vis.get_attr_by_channel("x")[0]
y_attr = self.vis.get_attr_by_channel("y")[0]
x_attr_abv = str(x_attr.attribute)
y_attr_abv = str(y_attr.attribute)
if len(x_attr_abv) > 25:
x_attr_abv = x_attr.attribute[:15] + "..." + x_attr.attribute[-10:]
if len(y_attr_abv) > 25:
y_attr_abv = y_attr.attribute[:15] + "..." + y_attr.attribute[-10:]
if isinstance(x_attr.attribute, str):
x_attr.attribute = x_attr.attribute.replace(".", "")
if isinstance(y_attr.attribute, str):
y_attr.attribute = y_attr.attribute.replace(".", "")
# Remove NaNs only for Line Charts (offsets axis range)
self.data = self.data.dropna(
subset=[x_attr.attribute, y_attr.attribute])
self.code += "import altair as alt\n"
self.code += "import pandas._libs.tslibs.timestamps\n"
self.code += "from pandas._libs.tslibs.timestamps import Timestamp\n"
self.code += f"visData = pd.DataFrame({str(self.data.to_dict())})\n"
if y_attr.data_model == "measure":
agg_title = get_agg_title(y_attr)
x_attr_spec = alt.X(str(x_attr.attribute),
type=x_attr.data_type,
axis=alt.Axis(title=x_attr_abv))
y_attr_spec = alt.Y(
str(y_attr.attribute),
type=y_attr.data_type,
title=agg_title,
axis=alt.Axis(title=y_attr_abv),
)
x_attr_field_code = f"alt.X('{x_attr.attribute}', type = '{x_attr.data_type}', axis=alt.Axis(title='{x_attr_abv}'))"
y_attr_fieldCode = f"alt.Y('{y_attr.attribute}', type= '{y_attr.data_type}', title='{agg_title}', axis=alt.Axis(title='{y_attr_abv}')"
else:
agg_title = get_agg_title(x_attr)
x_attr_spec = alt.X(
str(x_attr.attribute),
type=x_attr.data_type,
title=agg_title,
axis=alt.Axis(title=x_attr_abv),
)
y_attr_spec = alt.Y(str(y_attr.attribute),
type=y_attr.data_type,
axis=alt.Axis(title=y_attr_abv))
x_attr_field_code = f"alt.X('{x_attr.attribute}', type = '{x_attr.data_type}', title='{agg_title}', axis=alt.Axis(title='{x_attr_abv}')"
y_attr_fieldCode = f"alt.Y('{y_attr.attribute}', type= '{y_attr.data_type}', axis=alt.Axis(title='{y_attr_abv}')"
self.data = AltairChart.sanitize_dataframe(self.data)
chart = alt.Chart(self.data).mark_line().encode(x=x_attr_spec,
y=y_attr_spec)
chart = chart.interactive() # Enable Zooming and Panning
self.code += f"""
chart = alt.Chart(visData).mark_line().encode(
y = {y_attr_fieldCode},
x = {x_attr_field_code},
)
chart = chart.interactive() # Enable Zooming and Panning
"""
return chart