def initialize_chart(self):
self.tooltip = False
x_attr = self.view.get_attr_by_channel("x")[0]
y_attr = self.view.get_attr_by_channel("y")[0]
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 (x_attr.data_model == "measure"):
agg_title = get_agg_title(x_attr)
y_attr_field = alt.Y(y_attr.attribute,
type=y_attr.data_type,
axis=alt.Axis(labelOverlap=True))
x_attr_field = alt.X(x_attr.attribute,
type=x_attr.data_type,
title=agg_title)
y_attr_field_code = f"alt.Y('{y_attr.attribute}', type= '{y_attr.data_type}', axis=alt.Axis(labelOverlap=True))"
x_attr_field_code = f"alt.X('{x_attr.attribute}', type= '{x_attr.data_type}', 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), sort ='-x')"
else:
agg_title = get_agg_title(y_attr)
x_attr_field = alt.X(x_attr.attribute,
type=x_attr.data_type,
axis=alt.Axis(labelOverlap=True))
y_attr_field = alt.Y(y_attr.attribute,
type=y_attr.data_type,
title=agg_title)
x_attr_field_code = f"alt.X('{x_attr.attribute}', type= '{x_attr.data_type}', axis=alt.Axis(labelOverlap=True))"
y_attr_field_code = f"alt.Y('{y_attr.attribute}', type= '{y_attr.data_type}', 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),sort='-y')"
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
chart = chart.configure_mark(tooltip=alt.TooltipContent(
'encoding')) # Setting tooltip as non-null
self.code += f'''
chart = alt.Chart(visData).mark_bar().encode(
y = {y_attr_field_code},
x = {x_attr_field_code},
)
chart = chart.configure_mark(tooltip=alt.TooltipContent('encoding')) # Setting tooltip as non-null
'''
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 = x_attr.attribute
y_attr_abv = y_attr.attribute
if len(x_attr.attribute) > 25:
x_attr_abv = x_attr.attribute[:15] + "..." + x_attr.attribute[-10:]
if len(y_attr.attribute) > 25:
y_attr_abv = y_attr.attribute[:15] + "..." + y_attr.attribute[-10:]
x_attr.attribute = x_attr.attribute.replace(".", "")
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(x_attr.attribute, type=x_attr.data_type, axis=alt.Axis(title=x_attr_abv))
y_attr_spec = alt.Y(
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(
x_attr.attribute, type=x_attr.data_type, title=agg_title, axis=alt.Axis(title=x_attr_abv)
)
y_attr_spec = alt.Y(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='{u_attr_abv}')"
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
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]
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(x_attr.attribute, type=x_attr.data_type)
y_attr_spec = alt.Y(y_attr.attribute,
type=y_attr.data_type,
title=agg_title)
x_attr_field_code = f"alt.X('{x_attr.attribute}', type = '{x_attr.data_type}')"
y_attr_fieldCode = (
f"alt.Y('{y_attr.attribute}', type= '{y_attr.data_type}', title='{agg_title}')"
)
else:
agg_title = get_agg_title(x_attr)
x_attr_spec = alt.X(x_attr.attribute,
type=x_attr.data_type,
title=agg_title)
y_attr_spec = alt.Y(y_attr.attribute, type=y_attr.data_type)
x_attr_field_code = (
f"alt.X('{x_attr.attribute}', type = '{x_attr.data_type}', title='{agg_title}')"
)
y_attr_fieldCode = f"alt.Y('{y_attr.attribute}', type= '{y_attr.data_type}')"
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
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
x_attr = self.vis.get_attr_by_channel("x")[0]
y_attr = self.vis.get_attr_by_channel("y")[0]
# Deal with overlong string axes labels
x_attr_abv = str(x_attr.attribute)
y_attr_abv = str(y_attr.attribute)
label_len = lux.config.label_len
prefix_len = prefix_len = math.ceil(3.0 * label_len / 5.0)
suffix_len = label_len - prefix_len
if len(x_attr_abv) > label_len:
x_attr_abv = x_attr.attribute[:prefix_len] + "..." + x_attr.attribute[-suffix_len:]
if len(y_attr_abv) > label_len:
y_attr_abv = y_attr.attribute[:prefix_len] + "..." + y_attr.attribute[-suffix_len:]
if x_attr.data_model == "measure":
agg_title = get_agg_title(x_attr)
measure_attr = x_attr.attribute
bar_attr = y_attr.attribute
else:
agg_title = get_agg_title(y_attr)
measure_attr = y_attr.attribute
bar_attr = x_attr.attribute
k = lux.config.number_of_bars
n_bars = len(self.data.iloc[:, 0].unique())
if n_bars > k: # Truncating to only top k
remaining_bars = n_bars - k
self.data = self.data.nlargest(k, measure_attr)
self.ax.text(
0.95,
0.01,
f"+ {remaining_bars} more ...",
verticalalignment="bottom",
horizontalalignment="right",
transform=self.ax.transAxes,
fontsize=11,
fontweight="bold",
color="#ff8e04",
)
df = self.data
bar = df[bar_attr].apply(lambda x: str(x))
bars = list(bar)
measurements = list(df[measure_attr])
plot_code = ""
color_attr = self.vis.get_attr_by_channel("color")
if len(color_attr) == 1:
self.fig, self.ax = matplotlib_setup(6, 4)
color_attr_name = color_attr[0].attribute
colors = df[color_attr_name].values
unique = list(set(colors))
d_x = {}
d_y = {}
for i in unique:
d_x[i] = []
d_y[i] = []
for i in range(len(colors)):
d_x[colors[i]].append(bars[i])
d_y[colors[i]].append(measurements[i])
for i in range(len(unique)):
xval = d_x[unique[i]]
yval = d_y[unique[i]]
l = unique[i]
self.ax.barh(xval, yval, label=l)
plot_code += f"ax.barh({xval},{yval}, label='{l}')\n"
self.ax.legend(
title=color_attr_name, bbox_to_anchor=(1.05, 1), loc="upper left", ncol=1, frameon=False
)
plot_code += f"""ax.legend(title='{color_attr_name}',
bbox_to_anchor=(1.05, 1),
loc='upper left',
ncol=1,
frameon=False)\n"""
else:
self.ax.barh(bar, df[measure_attr], align="center")
plot_code += f"ax.barh({bar}, {df[measure_attr]}, align='center')\n"
y_ticks_abbev = df[bar_attr].apply(lambda x: str(x)[:10] + "..." if len(str(x)) > 10 else str(x))
self.ax.set_yticks(bars)
self.ax.set_yticklabels(y_ticks_abbev)
self.ax.set_xlabel(x_attr_abv)
self.ax.set_ylabel(y_attr_abv)
plt.gca().invert_yaxis()
self.code += "import numpy as np\n"
self.code += "from math import nan\n"
self.code += f"df = pd.DataFrame({str(self.data.to_dict())})\n"
self.code += f"fig, ax = plt.subplots()\n"
self.code += f"bars = df['{bar_attr}']\n"
self.code += f"measurements = df['{measure_attr}']\n"
self.code += plot_code
self.code += f"ax.set_xlabel('{x_attr_abv}')\n"
self.code += f"ax.set_ylabel('{y_attr_abv}')\n"
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]
if x_attr.data_model == "measure":
agg_title = get_agg_title(x_attr)
measure_attr = x_attr.attribute
bar_attr = y_attr.attribute
y_attr_field = alt.Y(
y_attr.attribute,
type=y_attr.data_type,
axis=alt.Axis(labelOverlap=True),
)
x_attr_field = alt.X(x_attr.attribute,
type=x_attr.data_type,
title=agg_title)
y_attr_field_code = f"alt.Y('{y_attr.attribute}', type= '{y_attr.data_type}', axis=alt.Axis(labelOverlap=True))"
x_attr_field_code = f"alt.X('{x_attr.attribute}', type= '{x_attr.data_type}', 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), sort ='-x')"
else:
agg_title = get_agg_title(y_attr)
measure_attr = y_attr.attribute
bar_attr = x_attr.attribute
x_attr_field = alt.X(
x_attr.attribute,
type=x_attr.data_type,
axis=alt.Axis(labelOverlap=True),
)
y_attr_field = alt.Y(y_attr.attribute,
type=y_attr.data_type,
title=agg_title)
x_attr_field_code = f"alt.X('{x_attr.attribute}', type= '{x_attr.data_type}', axis=alt.Axis(labelOverlap=True))"
y_attr_field_code = f"alt.Y('{y_attr.attribute}', type= '{y_attr.data_type}', 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),sort='-y')"
k = 10
self._topkcode = ""
n_bars = len(self.data[bar_attr].unique())
if n_bars > k: # Truncating to only top k
remaining_bars = n_bars - k
self.data = self.data.nlargest(k, measure_attr)
self.text = alt.Chart(self.data).mark_text(
x=155,
y=142,
align="right",
color="#ff8e04",
fontSize=11,
text=f"+ {remaining_bars} more ...",
)
self._topkcode = f"""text = alt.Chart(visData).mark_text(
x=155,
y=142,
align="right",
color = "#ff8e04",
fontSize = 11,
text=f"+ {remaining_bars} more ..."
)
chart = chart + text\n"""
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 # 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 = x_attr.attribute
y_attr_abv = y_attr.attribute
if len(x_attr.attribute) > 25:
x_attr_abv = x_attr.attribute[:15] + "..." + x_attr.attribute[-10:]
if len(y_attr.attribute) > 25:
y_attr_abv = y_attr.attribute[:15] + "..." + y_attr.attribute[-10:]
self.data = self.data.dropna(
subset=[x_attr.attribute, y_attr.attribute])
df = pd.DataFrame(self.data)
x_pts = df[x_attr.attribute]
y_pts = df[y_attr.attribute]
plot_code = ""
color_attr = self.vis.get_attr_by_channel("color")
if len(color_attr) == 1:
self.fig, self.ax = matplotlib_setup(6, 4)
color_attr_name = color_attr[0].attribute
color_attr_type = color_attr[0].data_type
colors = df[color_attr_name].values
unique = list(set(colors))
d_x = {}
d_y = {}
for i in unique:
d_x[i] = []
d_y[i] = []
for i in range(len(colors)):
d_x[colors[i]].append(x_pts[i])
d_y[colors[i]].append(y_pts[i])
for i in range(len(unique)):
self.ax.plot(d_x[unique[i]], d_y[unique[i]], label=unique[i])
plot_code += f"""ax.plot(
{d_x}[{unique}[{i}]],
{d_y}[{unique}[{i}]],
label={unique}[{i}])\n"""
self.ax.legend(title=color_attr_name,
bbox_to_anchor=(1.05, 1),
loc="upper left",
ncol=1,
frameon=False)
plot_code += f"""ax.legend(
title='{color_attr_name}',
bbox_to_anchor=(1.05, 1),
loc='upper left',
ncol=1,
frameon=False,)\n"""
else:
self.ax.plot(x_pts, y_pts)
plot_code += f"ax.plot(x_pts, y_pts)\n"
x_label = ""
y_label = ""
if y_attr.data_model == "measure":
agg_title = get_agg_title(y_attr)
self.ax.set_xlabel(x_attr_abv)
self.ax.set_ylabel(agg_title)
x_label = x_attr_abv
y_label = agg_title
else:
agg_title = get_agg_title(x_attr)
self.ax.set_xlabel(agg_title)
self.ax.set_ylabel(y_attr_abv)
x_label = agg_title
y_label = y_attr_abv
self.code += "import numpy as np\n"
self.code += "from math import nan\n"
self.code += f"fig, ax = plt.subplots()\n"
self.code += f"x_pts = df['{x_attr.attribute}']\n"
self.code += f"y_pts = df['{y_attr.attribute}']\n"
self.code += plot_code
self.code += f"ax.set_xlabel('{x_label}')\n"
self.code += f"ax.set_ylabel('{y_label}')\n"
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 = x_attr.attribute
y_attr_abv = y_attr.attribute
if len(x_attr.attribute) > 25:
x_attr_abv = x_attr.attribute[:15] + "..." + x_attr.attribute[-10:]
if len(y_attr.attribute) > 25:
y_attr_abv = y_attr.attribute[:15] + "..." + y_attr.attribute[-10:]
if x_attr.data_model == "measure":
agg_title = get_agg_title(x_attr)
measure_attr = x_attr.attribute
bar_attr = y_attr.attribute
else:
agg_title = get_agg_title(y_attr)
measure_attr = y_attr.attribute
bar_attr = x_attr.attribute
k = 10
self._topkcode = ""
n_bars = len(self.data.iloc[:, 0].unique())
if n_bars > k: # Truncating to only top k
remaining_bars = n_bars - k
self.data = self.data.nlargest(k, measure_attr)
self.ax.text(
0.95,
0.01,
f"+ {remaining_bars} more ...",
verticalalignment="bottom",
horizontalalignment="right",
transform=self.ax.transAxes,
fontsize=11,
fontweight="bold",
color="#ff8e04",
)
self._topkcode = f"""text = alt.Chart(visData).mark_text(
x=155,
y=142,
align="right",
color = "#ff8e04",
fontSize = 11,
text=f"+ {remaining_bars} more ..."
)
chart = chart + text\n"""
df = pd.DataFrame(self.data)
bars = df[bar_attr].apply(lambda x: str(x))
measurements = df[measure_attr]
plot_code = ""
color_attr = self.vis.get_attr_by_channel("color")
if len(color_attr) == 1:
self.fig, self.ax = matplotlib_setup(6, 4)
color_attr_name = color_attr[0].attribute
color_attr_type = color_attr[0].data_type
colors = df[color_attr_name].values
unique = list(set(colors))
d_x = {}
d_y = {}
for i in unique:
d_x[i] = []
d_y[i] = []
for i in range(len(colors)):
d_x[colors[i]].append(bars[i])
d_y[colors[i]].append(measurements[i])
for i in range(len(unique)):
self.ax.barh(d_x[unique[i]], d_y[unique[i]], label=unique[i])
plot_code += (
f"ax.barh({d_x}[{unique}[{i}]], {d_y}[{unique}[{i}]], label={unique}[{i}])\n"
)
self.ax.legend(title=color_attr_name,
bbox_to_anchor=(1.05, 1),
loc="upper left",
ncol=1,
frameon=False)
plot_code += f"""ax.legend(
title='{color_attr_name}',
bbox_to_anchor=(1.05, 1),
loc='upper left',
ncol=1,
frameon=False,)\n"""
else:
self.ax.barh(bars, measurements, align="center")
plot_code += f"ax.barh(bars, measurements, align='center')\n"
y_ticks_abbev = df[bar_attr].apply(lambda x: str(x)[:10] + "..."
if len(str(x)) > 10 else str(x))
self.ax.set_yticks(bars)
self.ax.set_yticklabels(y_ticks_abbev)
self.ax.set_xlabel(x_attr_abv)
self.ax.set_ylabel(y_attr_abv)
plt.gca().invert_yaxis()
self.code += "import numpy as np\n"
self.code += "from math import nan\n"
self.code += f"fig, ax = plt.subplots()\n"
self.code += f"bars = df['{bar_attr}']\n"
self.code += f"measurements = df['{measure_attr}']\n"
self.code += plot_code
self.code += f"ax.set_xlabel('{x_attr_abv}')\n"
self.code += f"ax.set_ylabel('{y_attr_abv}')\n"
