PX internals renaming#2135

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Merged
nicolaskruchten merged 6 commits into from
Jan 31, 2020
Merged

PX internals renaming #2135

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d7fc1bc
tweaks to make flake8 happy
nicolaskruchten Jan 28, 2020
e9fa00d
g -> trace_data
nicolaskruchten Jan 28, 2020
ca87353
k -> attr_name
nicolaskruchten Jan 28, 2020
e7ced12
v -> attr_value
nicolaskruchten Jan 28, 2020
94303bc
v_label -> attr_label
nicolaskruchten Jan 28, 2020
95f78c2
result -> trace_patch
nicolaskruchten Jan 28, 2020
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207 changes: 110 additions & 97 deletions packages/python/plotly/plotly/express/_core.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -137,7 +137,7 @@ def make_mapping(args, variable):
)


def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
"""Populates a dict with arguments to update trace

Parameters
Expand All@@ -147,7 +147,7 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
trace_spec : NamedTuple
which kind of trace to be used (has constructor, marginal etc.
attributes)
g : pandas DataFrame
trace_data : pandas DataFrame
data
mapping_labels : dict
to be used for hovertemplate
Expand All@@ -156,87 +156,92 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):

Returns
-------
result : dict
trace_patch : dict
dict to be used to update trace
fit_results : dict
fit information to be used for trendlines
"""
if "line_close" in args and args["line_close"]:
g = g.append(g.iloc[0])
result = trace_spec.trace_patch.copy() or {}
trace_data = trace_data.append(trace_data.iloc[0])
trace_patch = trace_spec.trace_patch.copy() or {}
fit_results = None
hover_header = ""
custom_data_len = 0
for k in trace_spec.attrs:
v = args[k]
v_label = get_decorated_label(args, v, k)
if k == "dimensions":
for attr_name in trace_spec.attrs:
attr_value = args[attr_name]
attr_label = get_decorated_label(args, attr_value, attr_name)
if attr_name == "dimensions":
dims = [
(name, column)
for (name, column) in g.iteritems()
if ((not v) or (name in v))
for (name, column) in trace_data.iteritems()
if ((not attr_value) or (name in attr_value))
and (
trace_spec.constructor != go.Parcoords
or args["data_frame"][name].dtype.kind in "bifc"
)
and (
trace_spec.constructor != go.Parcats
or (v is not None and name in v)
or (attr_value is not None and name in attr_value)
or len(args["data_frame"][name].unique())
<= args["dimensions_max_cardinality"]
)
]
result["dimensions"] = [
trace_patch["dimensions"] = [
dict(label=get_label(args, name), values=column.values)
for (name, column) in dims
]
if trace_spec.constructor == go.Splom:
for d in result["dimensions"]:
for d in trace_patch["dimensions"]:
d["axis"] = dict(matches=True)
mapping_labels["%{xaxis.title.text}"] = "%{x}"
mapping_labels["%{yaxis.title.text}"] = "%{y}"

elif (
v is not None
or (trace_spec.constructor == go.Histogram and k in ["x", "y"])
attr_value is not None
or (trace_spec.constructor == go.Histogram and attr_name in ["x", "y"])
or (
trace_spec.constructor in [go.Histogram2d, go.Histogram2dContour]
and k == "z"
and attr_name == "z"
)
):
if k == "size":
if "marker" not in result:
result["marker"] = dict()
result["marker"]["size"] = g[v]
result["marker"]["sizemode"] = "area"
result["marker"]["sizeref"] = sizeref
mapping_labels[v_label] = "%{marker.size}"
elif k == "marginal_x":
if attr_name == "size":
if "marker" not in trace_patch:
trace_patch["marker"] = dict()
trace_patch["marker"]["size"] = trace_data[attr_value]
trace_patch["marker"]["sizemode"] = "area"
trace_patch["marker"]["sizeref"] = sizeref
mapping_labels[attr_label] = "%{marker.size}"
elif attr_name == "marginal_x":
if trace_spec.constructor == go.Histogram:
mapping_labels["count"] = "%{y}"
elif k == "marginal_y":
elif attr_name == "marginal_y":
if trace_spec.constructor == go.Histogram:
mapping_labels["count"] = "%{x}"
elif k == "trendline":
if v in ["ols", "lowess"] and args["x"] and args["y"] and len(g) > 1:
elif attr_name == "trendline":
if (
attr_value in ["ols", "lowess"]
and args["x"]
and args["y"]
and len(trace_data) > 1
):
import statsmodels.api as sm

# sorting is bad but trace_specs with "trendline" have no other attrs
g2 = g.sort_values(by=args["x"])
y = g2[args["y"]]
x = g2[args["x"]]
result["x"] = x
sorted_trace_data = trace_data.sort_values(by=args["x"])
y = sorted_trace_data[args["y"]]
x = sorted_trace_data[args["x"]]
trace_patch["x"] = x

if x.dtype.type == np.datetime64:
x = x.astype(int) / 10 ** 9 # convert to unix epoch seconds

if v == "lowess":
if attr_value == "lowess":
trendline = sm.nonparametric.lowess(y, x)
result["y"] = trendline[:, 1]
trace_patch["y"] = trendline[:, 1]
hover_header = "<b>LOWESS trendline</b><br><br>"
elif v == "ols":
elif attr_value == "ols":
fit_results = sm.OLS(y.values, sm.add_constant(x.values)).fit()
result["y"] = fit_results.predict()
trace_patch["y"] = fit_results.predict()
hover_header = "<b>OLS trendline</b><br>"
hover_header += "%s = %g * %s + %g<br>" % (
args["y"],
Expand All@@ -250,120 +255,127 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
mapping_labels[get_label(args, args["x"])] = "%{x}"
mapping_labels[get_label(args, args["y"])] = "%{y} <b>(trend)</b>"

elif k.startswith("error"):
error_xy = k[:7]
arr = "arrayminus" if k.endswith("minus") else "array"
if error_xy not in result:
result[error_xy] = {}
result[error_xy][arr] = g[v]
elif k == "custom_data":
result["customdata"] = g[v].values
custom_data_len = len(v) # number of custom data columns
elif k == "hover_name":
elif attr_name.startswith("error"):
error_xy = attr_name[:7]
arr = "arrayminus" if attr_name.endswith("minus") else "array"
if error_xy not in trace_patch:
trace_patch[error_xy] = {}
trace_patch[error_xy][arr] = trace_data[attr_value]
elif attr_name == "custom_data":
trace_patch["customdata"] = trace_data[attr_value].values
custom_data_len = len(attr_value) # number of custom data columns
elif attr_name == "hover_name":
if trace_spec.constructor not in [
go.Histogram,
go.Histogram2d,
go.Histogram2dContour,
]:
result["hovertext"] = g[v]
trace_patch["hovertext"] = trace_data[attr_value]
if hover_header == "":
hover_header = "<b>%{hovertext}</b><br><br>"
elif k == "hover_data":
elif attr_name == "hover_data":
if trace_spec.constructor not in [
go.Histogram,
go.Histogram2d,
go.Histogram2dContour,
]:
for col in v:
for col in attr_value:
try:
position = args["custom_data"].index(col)
except (ValueError, AttributeError, KeyError):
position = custom_data_len
custom_data_len += 1
if "customdata" in result:
result["customdata"] = np.hstack(
(result["customdata"], g[col].values[:, None])
if "customdata" in trace_patch:
trace_patch["customdata"] = np.hstack(
(
trace_patch["customdata"],
trace_data[col].values[:, None],
)
)
else:
result["customdata"] = g[col].values[:, None]
v_label_col = get_decorated_label(args, col, None)
mapping_labels[v_label_col] = "%%{customdata[%d]}" % (position)
elif k == "color":
trace_patch["customdata"] = trace_data[col].values[
:, None
]
attr_label_col = get_decorated_label(args, col, None)
mapping_labels[attr_label_col] = "%%{customdata[%d]}" % (
position
)
elif attr_name == "color":
if trace_spec.constructor in [go.Choropleth, go.Choroplethmapbox]:
result["z"] = g[v]
result["coloraxis"] = "coloraxis1"
mapping_labels[v_label] = "%{z}"
trace_patch["z"] = trace_data[attr_value]
trace_patch["coloraxis"] = "coloraxis1"
mapping_labels[attr_label] = "%{z}"
elif trace_spec.constructor in [
go.Sunburst,
go.Treemap,
go.Pie,
go.Funnelarea,
]:
if "marker" not in result:
result["marker"] = dict()
if "marker" not in trace_patch:
trace_patch["marker"] = dict()

if args.get("color_is_continuous"):
result["marker"]["colors"] = g[v]
result["marker"]["coloraxis"] = "coloraxis1"
mapping_labels[v_label] = "%{color}"
trace_patch["marker"]["colors"] = trace_data[attr_value]
trace_patch["marker"]["coloraxis"] = "coloraxis1"
mapping_labels[attr_label] = "%{color}"
else:
result["marker"]["colors"] = []
trace_patch["marker"]["colors"] = []
mapping = {}
for cat in g[v]:
for cat in trace_data[attr_value]:
if mapping.get(cat) is None:
mapping[cat] = args["color_discrete_sequence"][
len(mapping) % len(args["color_discrete_sequence"])
]
result["marker"]["colors"].append(mapping[cat])
trace_patch["marker"]["colors"].append(mapping[cat])
else:
colorable = "marker"
if trace_spec.constructor in [go.Parcats, go.Parcoords]:
colorable = "line"
if colorable not in result:
result[colorable] = dict()
result[colorable]["color"] = g[v]
result[colorable]["coloraxis"] = "coloraxis1"
mapping_labels[v_label] = "%%{%s.color}" % colorable
elif k == "animation_group":
result["ids"] = g[v]
elif k == "locations":
result[k] = g[v]
mapping_labels[v_label] = "%{location}"
elif k == "values":
result[k] = g[v]
_label = "value" if v_label == "values" else v_label
if colorable not in trace_patch:
trace_patch[colorable] = dict()
trace_patch[colorable]["color"] = trace_data[attr_value]
trace_patch[colorable]["coloraxis"] = "coloraxis1"
mapping_labels[attr_label] = "%%{%s.color}" % colorable
elif attr_name == "animation_group":
trace_patch["ids"] = trace_data[attr_value]
elif attr_name == "locations":
trace_patch[attr_name] = trace_data[attr_value]
mapping_labels[attr_label] = "%{location}"
elif attr_name == "values":
trace_patch[attr_name] = trace_data[attr_value]
_label = "value" if attr_label == "values" else attr_label
mapping_labels[_label] = "%{value}"
elif k == "parents":
result[k] = g[v]
_label = "parent" if v_label == "parents" else v_label
elif attr_name == "parents":
trace_patch[attr_name] = trace_data[attr_value]
_label = "parent" if attr_label == "parents" else attr_label
mapping_labels[_label] = "%{parent}"
elif k == "ids":
result[k] = g[v]
_label = "id" if v_label == "ids" else v_label
elif attr_name == "ids":
trace_patch[attr_name] = trace_data[attr_value]
_label = "id" if attr_label == "ids" else attr_label
mapping_labels[_label] = "%{id}"
elif k == "names":
elif attr_name == "names":
if trace_spec.constructor in [
go.Sunburst,
go.Treemap,
go.Pie,
go.Funnelarea,
]:
result["labels"] = g[v]
_label = "label" if v_label == "names" else v_label
trace_patch["labels"] = trace_data[attr_value]
_label = "label" if attr_label == "names" else attr_label
mapping_labels[_label] = "%{label}"
else:
result[k] = g[v]
trace_patch[attr_name] = trace_data[attr_value]
else:
if v:
result[k] = g[v]
mapping_labels[v_label] = "%%{%s}" % k
if attr_value:
trace_patch[attr_name] = trace_data[attr_value]
mapping_labels[attr_label] = "%%{%s}" % attr_name
if trace_spec.constructor not in [
go.Parcoords,
go.Parcats,
]:
hover_lines = [k + "=" + v for k, v in mapping_labels.items()]
result["hovertemplate"] = hover_header + "<br>".join(hover_lines)
return result, fit_results
trace_patch["hovertemplate"] = hover_header + "<br>".join(hover_lines)
return trace_patch, fit_results


def configure_axes(args, constructor, fig, orders):
Expand DownExpand Up@@ -1015,8 +1027,8 @@ def _check_dataframe_all_leaves(df):
null_indices = np.nonzero(null_mask.any(axis=1).values)[0]
for null_row_index in null_indices:
row = null_mask.iloc[null_row_index]
indices = np.nonzero(row.values)[0]
if not row[indices[0] :].all():
i = np.nonzero(row.values)[0][0]
if not row[i:].all():
raise ValueError(
"None entries cannot have not-None children",
df_sorted.iloc[null_row_index],
Expand DownExpand Up@@ -1058,6 +1070,7 @@ def process_dataframe_hierarchy(args):
path = [new_col_name if x == col_name else x for x in path]
df[new_col_name] = series_to_copy
# ------------ Define aggregation functions --------------------------------

def aggfunc_discrete(x):
uniques = x.unique()
if len(uniques) == 1:
Expand Down
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codeBlock.parentElement.setAttribute('data-copy-added', 'true');
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btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';
btn.onmouseover = function() { this.style.opacity = '1'; };
btn.onmouseout = function() { this.style.opacity = '0.7'; };
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})();
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PX internals renaming#2135

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 Merged

nicolaskruchten
merged 6 commits into

from

Jan 31, 2020
 Merged


PX internals renaming
#2135
 Changes from all commits
Commits

Show all changes


6 commits


Select commit
Hold shift + click to select a range
d7fc1bc

tweaks to make flake8 happy


nicolaskruchten Jan 28, 2020
e9fa00d

g -> trace_data


nicolaskruchten Jan 28, 2020
ca87353

k -> attr_name


nicolaskruchten Jan 28, 2020
e7ced12

v -> attr_value


nicolaskruchten Jan 28, 2020
94303bc

v_label -> attr_label


nicolaskruchten Jan 28, 2020
95f78c2

result -> trace_patch


nicolaskruchten Jan 28, 2020

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207 changes: 110 additions & 97 deletions
packages/python/plotly/plotly/express/_core.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -137,7 +137,7 @@ def make_mapping(args, variable):
 )


def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
 """Populates a dict with arguments to update trace

 Parameters
Expand All@@ -147,7 +147,7 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 trace_spec : NamedTuple
 which kind of trace to be used (has constructor, marginal etc.
 attributes)
g : pandas DataFrame
trace_data : pandas DataFrame
 data
 mapping_labels : dict
 to be used for hovertemplate
Expand All@@ -156,87 +156,92 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):

 Returns
 -------
result : dict
trace_patch : dict
 dict to be used to update trace
 fit_results : dict
 fit information to be used for trendlines
 """
 if "line_close" in args and args["line_close"]:
g = g.append(g.iloc[0])
result = trace_spec.trace_patch.copy() or {}
trace_data = trace_data.append(trace_data.iloc[0])
trace_patch = trace_spec.trace_patch.copy() or {}
 fit_results = None
 hover_header = ""
 custom_data_len = 0
 for k in trace_spec.attrs:
v = args[k]
v_label = get_decorated_label(args, v, k)
 if k == "dimensions":
 for attr_name in trace_spec.attrs:
attr_value = args[attr_name]
attr_label = get_decorated_label(args, attr_value, attr_name)
 if attr_name == "dimensions":
 dims = [
 (name, column)
 for (name, column) in g.iteritems()
 if ((not v) or (name in v))
 for (name, column) in trace_data.iteritems()
 if ((not attr_value) or (name in attr_value))
 and (
 trace_spec.constructor != go.Parcoords
 or args["data_frame"][name].dtype.kind in "bifc"
 )
 and (
 trace_spec.constructor != go.Parcats
 or (v is not None and name in v)
 or (attr_value is not None and name in attr_value)
 or len(args["data_frame"][name].unique())
 <= args["dimensions_max_cardinality"]
 )
 ]
result["dimensions"] = [
trace_patch["dimensions"] = [
 dict(label=get_label(args, name), values=column.values)
 for (name, column) in dims
 ]
 if trace_spec.constructor == go.Splom:
 for d in result["dimensions"]:
 for d in trace_patch["dimensions"]:
 d["axis"] = dict(matches=True)
 mapping_labels["%{xaxis.title.text}"] = "%{x}"
 mapping_labels["%{yaxis.title.text}"] = "%{y}"

 elif (
v is not None
 or (trace_spec.constructor == go.Histogram and k in ["x", "y"])
attr_value is not None
 or (trace_spec.constructor == go.Histogram and attr_name in ["x", "y"])
 or (
 trace_spec.constructor in [go.Histogram2d, go.Histogram2dContour]
 and k == "z"
 and attr_name == "z"
 )
 ):
 if k == "size":
 if "marker" not in result:
result["marker"] = dict()
result["marker"]["size"] = g[v]
result["marker"]["sizemode"] = "area"
result["marker"]["sizeref"] = sizeref
 mapping_labels[v_label] = "%{marker.size}"
 elif k == "marginal_x":
 if attr_name == "size":
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()
trace_patch["marker"]["size"] = trace_data[attr_value]
trace_patch["marker"]["sizemode"] = "area"
trace_patch["marker"]["sizeref"] = sizeref
 mapping_labels[attr_label] = "%{marker.size}"
 elif attr_name == "marginal_x":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{y}"
 elif k == "marginal_y":
 elif attr_name == "marginal_y":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{x}"
 elif k == "trendline":
 if v in ["ols", "lowess"] and args["x"] and args["y"] and len(g) > 1:
 elif attr_name == "trendline":
 if (
 attr_value in ["ols", "lowess"]
 and args["x"]
 and args["y"]
 and len(trace_data) > 1
 ):
 import statsmodels.api as sm

 # sorting is bad but trace_specs with "trendline" have no other attrs
g2 = g.sort_values(by=args["x"])
 y = g2[args["y"]]
 x = g2[args["x"]]
result["x"] = x
sorted_trace_data = trace_data.sort_values(by=args["x"])
 y = sorted_trace_data[args["y"]]
 x = sorted_trace_data[args["x"]]
trace_patch["x"] = x

 if x.dtype.type == np.datetime64:
 x = x.astype(int) / 10 ** 9 # convert to unix epoch seconds

 if v == "lowess":
 if attr_value == "lowess":
 trendline = sm.nonparametric.lowess(y, x)
result["y"] = trendline[:, 1]
trace_patch["y"] = trendline[:, 1]
 hover_header = "<b>LOWESS trendline</b><br><br>"
 elif v == "ols":
 elif attr_value == "ols":
 fit_results = sm.OLS(y.values, sm.add_constant(x.values)).fit()
result["y"] = fit_results.predict()
trace_patch["y"] = fit_results.predict()
 hover_header = "<b>OLS trendline</b><br>"
 hover_header += "%s = %g * %s + %g<br>" % (
 args["y"],
Expand All@@ -250,120 +255,127 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 mapping_labels[get_label(args, args["x"])] = "%{x}"
 mapping_labels[get_label(args, args["y"])] = "%{y} <b>(trend)</b>"

 elif k.startswith("error"):
 error_xy = k[:7]
 arr = "arrayminus" if k.endswith("minus") else "array"
 if error_xy not in result:
result[error_xy] = {}
result[error_xy][arr] = g[v]
 elif k == "custom_data":
result["customdata"] = g[v].values
 custom_data_len = len(v) # number of custom data columns
 elif k == "hover_name":
 elif attr_name.startswith("error"):
 error_xy = attr_name[:7]
 arr = "arrayminus" if attr_name.endswith("minus") else "array"
 if error_xy not in trace_patch:
trace_patch[error_xy] = {}
trace_patch[error_xy][arr] = trace_data[attr_value]
 elif attr_name == "custom_data":
trace_patch["customdata"] = trace_data[attr_value].values
 custom_data_len = len(attr_value) # number of custom data columns
 elif attr_name == "hover_name":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
result["hovertext"] = g[v]
trace_patch["hovertext"] = trace_data[attr_value]
 if hover_header == "":
 hover_header = "<b>%{hovertext}</b><br><br>"
 elif k == "hover_data":
 elif attr_name == "hover_data":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
 for col in v:
 for col in attr_value:
 try:
 position = args["custom_data"].index(col)
 except (ValueError, AttributeError, KeyError):
 position = custom_data_len
 custom_data_len += 1
 if "customdata" in result:
 result["customdata"] = np.hstack(
 (result["customdata"], g[col].values[:, None])
 if "customdata" in trace_patch:
 trace_patch["customdata"] = np.hstack(
 (
 trace_patch["customdata"],
 trace_data[col].values[:, None],
 )
 )
 else:
 result["customdata"] = g[col].values[:, None]
 v_label_col = get_decorated_label(args, col, None)
 mapping_labels[v_label_col] = "%%{customdata[%d]}" % (position)
 elif k == "color":
 trace_patch["customdata"] = trace_data[col].values[
 :, None
 ]
 attr_label_col = get_decorated_label(args, col, None)
 mapping_labels[attr_label_col] = "%%{customdata[%d]}" % (
 position
 )
 elif attr_name == "color":
 if trace_spec.constructor in [go.Choropleth, go.Choroplethmapbox]:
result["z"] = g[v]
result["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{z}"
trace_patch["z"] = trace_data[attr_value]
trace_patch["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{z}"
 elif trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
 if "marker" not in result:
result["marker"] = dict()
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()

 if args.get("color_is_continuous"):
result["marker"]["colors"] = g[v]
result["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{color}"
trace_patch["marker"]["colors"] = trace_data[attr_value]
trace_patch["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{color}"
 else:
result["marker"]["colors"] = []
trace_patch["marker"]["colors"] = []
 mapping = {}
 for cat in g[v]:
 for cat in trace_data[attr_value]:
 if mapping.get(cat) is None:
 mapping[cat] = args["color_discrete_sequence"][
 len(mapping) % len(args["color_discrete_sequence"])
 ]
result["marker"]["colors"].append(mapping[cat])
trace_patch["marker"]["colors"].append(mapping[cat])
 else:
 colorable = "marker"
 if trace_spec.constructor in [go.Parcats, go.Parcoords]:
 colorable = "line"
 if colorable not in result:
result[colorable] = dict()
result[colorable]["color"] = g[v]
result[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%%{%s.color}" % colorable
 elif k == "animation_group":
result["ids"] = g[v]
 elif k == "locations":
result[k] = g[v]
 mapping_labels[v_label] = "%{location}"
 elif k == "values":
result[k] = g[v]
 _label = "value" if v_label == "values" else v_label
 if colorable not in trace_patch:
trace_patch[colorable] = dict()
trace_patch[colorable]["color"] = trace_data[attr_value]
trace_patch[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%%{%s.color}" % colorable
 elif attr_name == "animation_group":
trace_patch["ids"] = trace_data[attr_value]
 elif attr_name == "locations":
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%{location}"
 elif attr_name == "values":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "value" if attr_label == "values" else attr_label
 mapping_labels[_label] = "%{value}"
 elif k == "parents":
result[k] = g[v]
 _label = "parent" if v_label == "parents" else v_label
 elif attr_name == "parents":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "parent" if attr_label == "parents" else attr_label
 mapping_labels[_label] = "%{parent}"
 elif k == "ids":
result[k] = g[v]
 _label = "id" if v_label == "ids" else v_label
 elif attr_name == "ids":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "id" if attr_label == "ids" else attr_label
 mapping_labels[_label] = "%{id}"
 elif k == "names":
 elif attr_name == "names":
 if trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
result["labels"] = g[v]
 _label = "label" if v_label == "names" else v_label
trace_patch["labels"] = trace_data[attr_value]
 _label = "label" if attr_label == "names" else attr_label
 mapping_labels[_label] = "%{label}"
 else:
result[k] = g[v]
trace_patch[attr_name] = trace_data[attr_value]
 else:
 if v:
result[k] = g[v]
 mapping_labels[v_label] = "%%{%s}" % k
 if attr_value:
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%%{%s}" % attr_name
 if trace_spec.constructor not in [
 go.Parcoords,
 go.Parcats,
 ]:
 hover_lines = [k + "=" + v for k, v in mapping_labels.items()]
result["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return result, fit_results
trace_patch["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return trace_patch, fit_results


def configure_axes(args, constructor, fig, orders):
Expand DownExpand Up@@ -1015,8 +1027,8 @@ def _check_dataframe_all_leaves(df):
 null_indices = np.nonzero(null_mask.any(axis=1).values)[0]
 for null_row_index in null_indices:
 row = null_mask.iloc[null_row_index]
indices = np.nonzero(row.values)[0]
 if not row[indices[0] :].all():
i = np.nonzero(row.values)[0][0]
 if not row[i:].all():
 raise ValueError(
 "None entries cannot have not-None children",
 df_sorted.iloc[null_row_index],
Expand DownExpand Up@@ -1058,6 +1070,7 @@ def process_dataframe_hierarchy(args):
 path = [new_col_name if x == col_name else x for x in path]
 df[new_col_name] = series_to_copy
 # ------------ Define aggregation functions --------------------------------

 def aggfunc_discrete(x):
 uniques = x.unique()
 if len(uniques) == 1:
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Force GitHub README to respect dark mode
(function() {
var style = document.createElement('style');
style.textContent = '
.markdown-body {
color-scheme: dark light;
}
.markdown-body pre { background: #161b22 !important; }
.markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }
.markdown-body table th, .markdown-body table td { border-color: #30363d !important; }
.markdown-body img { background: #0d1117; }
.markdown-body blockquote { border-left-color: #8b949e; }
.markdown-body hr { border-color: #30363d; }
';
document.head.appendChild(style);
})();
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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PX internals renaming#2135

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 Merged

nicolaskruchten
merged 6 commits into

from

Jan 31, 2020
 Merged


PX internals renaming
#2135
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d7fc1bc

tweaks to make flake8 happy


nicolaskruchten Jan 28, 2020
e9fa00d

g -> trace_data


nicolaskruchten Jan 28, 2020
ca87353

k -> attr_name


nicolaskruchten Jan 28, 2020
e7ced12

v -> attr_value


nicolaskruchten Jan 28, 2020
94303bc

v_label -> attr_label


nicolaskruchten Jan 28, 2020
95f78c2

result -> trace_patch


nicolaskruchten Jan 28, 2020

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207 changes: 110 additions & 97 deletions
packages/python/plotly/plotly/express/_core.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -137,7 +137,7 @@ def make_mapping(args, variable):
 )


def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
 """Populates a dict with arguments to update trace

 Parameters
Expand All@@ -147,7 +147,7 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 trace_spec : NamedTuple
 which kind of trace to be used (has constructor, marginal etc.
 attributes)
g : pandas DataFrame
trace_data : pandas DataFrame
 data
 mapping_labels : dict
 to be used for hovertemplate
Expand All@@ -156,87 +156,92 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):

 Returns
 -------
result : dict
trace_patch : dict
 dict to be used to update trace
 fit_results : dict
 fit information to be used for trendlines
 """
 if "line_close" in args and args["line_close"]:
g = g.append(g.iloc[0])
result = trace_spec.trace_patch.copy() or {}
trace_data = trace_data.append(trace_data.iloc[0])
trace_patch = trace_spec.trace_patch.copy() or {}
 fit_results = None
 hover_header = ""
 custom_data_len = 0
 for k in trace_spec.attrs:
v = args[k]
v_label = get_decorated_label(args, v, k)
 if k == "dimensions":
 for attr_name in trace_spec.attrs:
attr_value = args[attr_name]
attr_label = get_decorated_label(args, attr_value, attr_name)
 if attr_name == "dimensions":
 dims = [
 (name, column)
 for (name, column) in g.iteritems()
 if ((not v) or (name in v))
 for (name, column) in trace_data.iteritems()
 if ((not attr_value) or (name in attr_value))
 and (
 trace_spec.constructor != go.Parcoords
 or args["data_frame"][name].dtype.kind in "bifc"
 )
 and (
 trace_spec.constructor != go.Parcats
 or (v is not None and name in v)
 or (attr_value is not None and name in attr_value)
 or len(args["data_frame"][name].unique())
 <= args["dimensions_max_cardinality"]
 )
 ]
result["dimensions"] = [
trace_patch["dimensions"] = [
 dict(label=get_label(args, name), values=column.values)
 for (name, column) in dims
 ]
 if trace_spec.constructor == go.Splom:
 for d in result["dimensions"]:
 for d in trace_patch["dimensions"]:
 d["axis"] = dict(matches=True)
 mapping_labels["%{xaxis.title.text}"] = "%{x}"
 mapping_labels["%{yaxis.title.text}"] = "%{y}"

 elif (
v is not None
 or (trace_spec.constructor == go.Histogram and k in ["x", "y"])
attr_value is not None
 or (trace_spec.constructor == go.Histogram and attr_name in ["x", "y"])
 or (
 trace_spec.constructor in [go.Histogram2d, go.Histogram2dContour]
 and k == "z"
 and attr_name == "z"
 )
 ):
 if k == "size":
 if "marker" not in result:
result["marker"] = dict()
result["marker"]["size"] = g[v]
result["marker"]["sizemode"] = "area"
result["marker"]["sizeref"] = sizeref
 mapping_labels[v_label] = "%{marker.size}"
 elif k == "marginal_x":
 if attr_name == "size":
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()
trace_patch["marker"]["size"] = trace_data[attr_value]
trace_patch["marker"]["sizemode"] = "area"
trace_patch["marker"]["sizeref"] = sizeref
 mapping_labels[attr_label] = "%{marker.size}"
 elif attr_name == "marginal_x":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{y}"
 elif k == "marginal_y":
 elif attr_name == "marginal_y":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{x}"
 elif k == "trendline":
 if v in ["ols", "lowess"] and args["x"] and args["y"] and len(g) > 1:
 elif attr_name == "trendline":
 if (
 attr_value in ["ols", "lowess"]
 and args["x"]
 and args["y"]
 and len(trace_data) > 1
 ):
 import statsmodels.api as sm

 # sorting is bad but trace_specs with "trendline" have no other attrs
g2 = g.sort_values(by=args["x"])
 y = g2[args["y"]]
 x = g2[args["x"]]
result["x"] = x
sorted_trace_data = trace_data.sort_values(by=args["x"])
 y = sorted_trace_data[args["y"]]
 x = sorted_trace_data[args["x"]]
trace_patch["x"] = x

 if x.dtype.type == np.datetime64:
 x = x.astype(int) / 10 ** 9 # convert to unix epoch seconds

 if v == "lowess":
 if attr_value == "lowess":
 trendline = sm.nonparametric.lowess(y, x)
result["y"] = trendline[:, 1]
trace_patch["y"] = trendline[:, 1]
 hover_header = "<b>LOWESS trendline</b><br><br>"
 elif v == "ols":
 elif attr_value == "ols":
 fit_results = sm.OLS(y.values, sm.add_constant(x.values)).fit()
result["y"] = fit_results.predict()
trace_patch["y"] = fit_results.predict()
 hover_header = "<b>OLS trendline</b><br>"
 hover_header += "%s = %g * %s + %g<br>" % (
 args["y"],
Expand All@@ -250,120 +255,127 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 mapping_labels[get_label(args, args["x"])] = "%{x}"
 mapping_labels[get_label(args, args["y"])] = "%{y} <b>(trend)</b>"

 elif k.startswith("error"):
 error_xy = k[:7]
 arr = "arrayminus" if k.endswith("minus") else "array"
 if error_xy not in result:
result[error_xy] = {}
result[error_xy][arr] = g[v]
 elif k == "custom_data":
result["customdata"] = g[v].values
 custom_data_len = len(v) # number of custom data columns
 elif k == "hover_name":
 elif attr_name.startswith("error"):
 error_xy = attr_name[:7]
 arr = "arrayminus" if attr_name.endswith("minus") else "array"
 if error_xy not in trace_patch:
trace_patch[error_xy] = {}
trace_patch[error_xy][arr] = trace_data[attr_value]
 elif attr_name == "custom_data":
trace_patch["customdata"] = trace_data[attr_value].values
 custom_data_len = len(attr_value) # number of custom data columns
 elif attr_name == "hover_name":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
result["hovertext"] = g[v]
trace_patch["hovertext"] = trace_data[attr_value]
 if hover_header == "":
 hover_header = "<b>%{hovertext}</b><br><br>"
 elif k == "hover_data":
 elif attr_name == "hover_data":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
 for col in v:
 for col in attr_value:
 try:
 position = args["custom_data"].index(col)
 except (ValueError, AttributeError, KeyError):
 position = custom_data_len
 custom_data_len += 1
 if "customdata" in result:
 result["customdata"] = np.hstack(
 (result["customdata"], g[col].values[:, None])
 if "customdata" in trace_patch:
 trace_patch["customdata"] = np.hstack(
 (
 trace_patch["customdata"],
 trace_data[col].values[:, None],
 )
 )
 else:
 result["customdata"] = g[col].values[:, None]
 v_label_col = get_decorated_label(args, col, None)
 mapping_labels[v_label_col] = "%%{customdata[%d]}" % (position)
 elif k == "color":
 trace_patch["customdata"] = trace_data[col].values[
 :, None
 ]
 attr_label_col = get_decorated_label(args, col, None)
 mapping_labels[attr_label_col] = "%%{customdata[%d]}" % (
 position
 )
 elif attr_name == "color":
 if trace_spec.constructor in [go.Choropleth, go.Choroplethmapbox]:
result["z"] = g[v]
result["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{z}"
trace_patch["z"] = trace_data[attr_value]
trace_patch["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{z}"
 elif trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
 if "marker" not in result:
result["marker"] = dict()
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()

 if args.get("color_is_continuous"):
result["marker"]["colors"] = g[v]
result["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{color}"
trace_patch["marker"]["colors"] = trace_data[attr_value]
trace_patch["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{color}"
 else:
result["marker"]["colors"] = []
trace_patch["marker"]["colors"] = []
 mapping = {}
 for cat in g[v]:
 for cat in trace_data[attr_value]:
 if mapping.get(cat) is None:
 mapping[cat] = args["color_discrete_sequence"][
 len(mapping) % len(args["color_discrete_sequence"])
 ]
result["marker"]["colors"].append(mapping[cat])
trace_patch["marker"]["colors"].append(mapping[cat])
 else:
 colorable = "marker"
 if trace_spec.constructor in [go.Parcats, go.Parcoords]:
 colorable = "line"
 if colorable not in result:
result[colorable] = dict()
result[colorable]["color"] = g[v]
result[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%%{%s.color}" % colorable
 elif k == "animation_group":
result["ids"] = g[v]
 elif k == "locations":
result[k] = g[v]
 mapping_labels[v_label] = "%{location}"
 elif k == "values":
result[k] = g[v]
 _label = "value" if v_label == "values" else v_label
 if colorable not in trace_patch:
trace_patch[colorable] = dict()
trace_patch[colorable]["color"] = trace_data[attr_value]
trace_patch[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%%{%s.color}" % colorable
 elif attr_name == "animation_group":
trace_patch["ids"] = trace_data[attr_value]
 elif attr_name == "locations":
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%{location}"
 elif attr_name == "values":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "value" if attr_label == "values" else attr_label
 mapping_labels[_label] = "%{value}"
 elif k == "parents":
result[k] = g[v]
 _label = "parent" if v_label == "parents" else v_label
 elif attr_name == "parents":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "parent" if attr_label == "parents" else attr_label
 mapping_labels[_label] = "%{parent}"
 elif k == "ids":
result[k] = g[v]
 _label = "id" if v_label == "ids" else v_label
 elif attr_name == "ids":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "id" if attr_label == "ids" else attr_label
 mapping_labels[_label] = "%{id}"
 elif k == "names":
 elif attr_name == "names":
 if trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
result["labels"] = g[v]
 _label = "label" if v_label == "names" else v_label
trace_patch["labels"] = trace_data[attr_value]
 _label = "label" if attr_label == "names" else attr_label
 mapping_labels[_label] = "%{label}"
 else:
result[k] = g[v]
trace_patch[attr_name] = trace_data[attr_value]
 else:
 if v:
result[k] = g[v]
 mapping_labels[v_label] = "%%{%s}" % k
 if attr_value:
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%%{%s}" % attr_name
 if trace_spec.constructor not in [
 go.Parcoords,
 go.Parcats,
 ]:
 hover_lines = [k + "=" + v for k, v in mapping_labels.items()]
result["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return result, fit_results
trace_patch["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return trace_patch, fit_results


def configure_axes(args, constructor, fig, orders):
Expand DownExpand Up@@ -1015,8 +1027,8 @@ def _check_dataframe_all_leaves(df):
 null_indices = np.nonzero(null_mask.any(axis=1).values)[0]
 for null_row_index in null_indices:
 row = null_mask.iloc[null_row_index]
indices = np.nonzero(row.values)[0]
 if not row[indices[0] :].all():
i = np.nonzero(row.values)[0][0]
 if not row[i:].all():
 raise ValueError(
 "None entries cannot have not-None children",
 df_sorted.iloc[null_row_index],
Expand DownExpand Up@@ -1058,6 +1070,7 @@ def process_dataframe_hierarchy(args):
 path = [new_col_name if x == col_name else x for x in path]
 df[new_col_name] = series_to_copy
 # ------------ Define aggregation functions --------------------------------

 def aggfunc_discrete(x):
 uniques = x.unique()
 if len(uniques) == 1:
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Highlight search terms from Google/DuckDuckGo/Bing referrer
(function() {
var ref = document.referrer;
var terms = [];
if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {
var url = new URL(ref);
var q = url.searchParams.get('q') || url.searchParams.get('p');
if (q) {
terms = q.split(/\s+/).filter(function(t) { return t.length > 2; });
}
}
if (terms.length === 0) return;
var style = document.createElement('style');
style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';
document.head.appendChild(style);
function highlight(node) {
if (node.nodeType === 3) { // text node
var text = node.textContent;
var found = false;
terms.forEach(function(term) {
var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi');
if (regex.test(text)) {
found = true;
var frag = document.createDocumentFragment();
var parts = text.split(regex);
parts.forEach(function(part, i) {
if (i % 2 === 0) {
frag.appendChild(document.createTextNode(part));
} else {
var span = document.createElement('span');
span.className = 'userscript-highlight';
span.textContent = part;
frag.appendChild(span);
}
});
node.parentNode.replaceChild(frag, node);
}
});
} else if (node.nodeType === 1 && node.childNodes) { // element
var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];
if (!skipTags.includes(node.tagName)) {
Array.from(node.childNodes).forEach(highlight);
}
}
}
highlight(document.body);
// Re-highlight on dynamic content
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1 || node.nodeType === 3) highlight(node);
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
PX internals renaming#2135

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 Merged

nicolaskruchten
merged 6 commits into

from

Jan 31, 2020
 Merged


PX internals renaming
#2135
 Changes from all commits
Commits

Show all changes


6 commits


Select commit
Hold shift + click to select a range
d7fc1bc

tweaks to make flake8 happy


nicolaskruchten Jan 28, 2020
e9fa00d

g -> trace_data


nicolaskruchten Jan 28, 2020
ca87353

k -> attr_name


nicolaskruchten Jan 28, 2020
e7ced12

v -> attr_value


nicolaskruchten Jan 28, 2020
94303bc

v_label -> attr_label


nicolaskruchten Jan 28, 2020
95f78c2

result -> trace_patch


nicolaskruchten Jan 28, 2020

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207 changes: 110 additions & 97 deletions
packages/python/plotly/plotly/express/_core.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -137,7 +137,7 @@ def make_mapping(args, variable):
 )


def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
 """Populates a dict with arguments to update trace

 Parameters
Expand All@@ -147,7 +147,7 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 trace_spec : NamedTuple
 which kind of trace to be used (has constructor, marginal etc.
 attributes)
g : pandas DataFrame
trace_data : pandas DataFrame
 data
 mapping_labels : dict
 to be used for hovertemplate
Expand All@@ -156,87 +156,92 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):

 Returns
 -------
result : dict
trace_patch : dict
 dict to be used to update trace
 fit_results : dict
 fit information to be used for trendlines
 """
 if "line_close" in args and args["line_close"]:
g = g.append(g.iloc[0])
result = trace_spec.trace_patch.copy() or {}
trace_data = trace_data.append(trace_data.iloc[0])
trace_patch = trace_spec.trace_patch.copy() or {}
 fit_results = None
 hover_header = ""
 custom_data_len = 0
 for k in trace_spec.attrs:
v = args[k]
v_label = get_decorated_label(args, v, k)
 if k == "dimensions":
 for attr_name in trace_spec.attrs:
attr_value = args[attr_name]
attr_label = get_decorated_label(args, attr_value, attr_name)
 if attr_name == "dimensions":
 dims = [
 (name, column)
 for (name, column) in g.iteritems()
 if ((not v) or (name in v))
 for (name, column) in trace_data.iteritems()
 if ((not attr_value) or (name in attr_value))
 and (
 trace_spec.constructor != go.Parcoords
 or args["data_frame"][name].dtype.kind in "bifc"
 )
 and (
 trace_spec.constructor != go.Parcats
 or (v is not None and name in v)
 or (attr_value is not None and name in attr_value)
 or len(args["data_frame"][name].unique())
 <= args["dimensions_max_cardinality"]
 )
 ]
result["dimensions"] = [
trace_patch["dimensions"] = [
 dict(label=get_label(args, name), values=column.values)
 for (name, column) in dims
 ]
 if trace_spec.constructor == go.Splom:
 for d in result["dimensions"]:
 for d in trace_patch["dimensions"]:
 d["axis"] = dict(matches=True)
 mapping_labels["%{xaxis.title.text}"] = "%{x}"
 mapping_labels["%{yaxis.title.text}"] = "%{y}"

 elif (
v is not None
 or (trace_spec.constructor == go.Histogram and k in ["x", "y"])
attr_value is not None
 or (trace_spec.constructor == go.Histogram and attr_name in ["x", "y"])
 or (
 trace_spec.constructor in [go.Histogram2d, go.Histogram2dContour]
 and k == "z"
 and attr_name == "z"
 )
 ):
 if k == "size":
 if "marker" not in result:
result["marker"] = dict()
result["marker"]["size"] = g[v]
result["marker"]["sizemode"] = "area"
result["marker"]["sizeref"] = sizeref
 mapping_labels[v_label] = "%{marker.size}"
 elif k == "marginal_x":
 if attr_name == "size":
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()
trace_patch["marker"]["size"] = trace_data[attr_value]
trace_patch["marker"]["sizemode"] = "area"
trace_patch["marker"]["sizeref"] = sizeref
 mapping_labels[attr_label] = "%{marker.size}"
 elif attr_name == "marginal_x":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{y}"
 elif k == "marginal_y":
 elif attr_name == "marginal_y":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{x}"
 elif k == "trendline":
 if v in ["ols", "lowess"] and args["x"] and args["y"] and len(g) > 1:
 elif attr_name == "trendline":
 if (
 attr_value in ["ols", "lowess"]
 and args["x"]
 and args["y"]
 and len(trace_data) > 1
 ):
 import statsmodels.api as sm

 # sorting is bad but trace_specs with "trendline" have no other attrs
g2 = g.sort_values(by=args["x"])
 y = g2[args["y"]]
 x = g2[args["x"]]
result["x"] = x
sorted_trace_data = trace_data.sort_values(by=args["x"])
 y = sorted_trace_data[args["y"]]
 x = sorted_trace_data[args["x"]]
trace_patch["x"] = x

 if x.dtype.type == np.datetime64:
 x = x.astype(int) / 10 ** 9 # convert to unix epoch seconds

 if v == "lowess":
 if attr_value == "lowess":
 trendline = sm.nonparametric.lowess(y, x)
result["y"] = trendline[:, 1]
trace_patch["y"] = trendline[:, 1]
 hover_header = "<b>LOWESS trendline</b><br><br>"
 elif v == "ols":
 elif attr_value == "ols":
 fit_results = sm.OLS(y.values, sm.add_constant(x.values)).fit()
result["y"] = fit_results.predict()
trace_patch["y"] = fit_results.predict()
 hover_header = "<b>OLS trendline</b><br>"
 hover_header += "%s = %g * %s + %g<br>" % (
 args["y"],
Expand All@@ -250,120 +255,127 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 mapping_labels[get_label(args, args["x"])] = "%{x}"
 mapping_labels[get_label(args, args["y"])] = "%{y} <b>(trend)</b>"

 elif k.startswith("error"):
 error_xy = k[:7]
 arr = "arrayminus" if k.endswith("minus") else "array"
 if error_xy not in result:
result[error_xy] = {}
result[error_xy][arr] = g[v]
 elif k == "custom_data":
result["customdata"] = g[v].values
 custom_data_len = len(v) # number of custom data columns
 elif k == "hover_name":
 elif attr_name.startswith("error"):
 error_xy = attr_name[:7]
 arr = "arrayminus" if attr_name.endswith("minus") else "array"
 if error_xy not in trace_patch:
trace_patch[error_xy] = {}
trace_patch[error_xy][arr] = trace_data[attr_value]
 elif attr_name == "custom_data":
trace_patch["customdata"] = trace_data[attr_value].values
 custom_data_len = len(attr_value) # number of custom data columns
 elif attr_name == "hover_name":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
result["hovertext"] = g[v]
trace_patch["hovertext"] = trace_data[attr_value]
 if hover_header == "":
 hover_header = "<b>%{hovertext}</b><br><br>"
 elif k == "hover_data":
 elif attr_name == "hover_data":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
 for col in v:
 for col in attr_value:
 try:
 position = args["custom_data"].index(col)
 except (ValueError, AttributeError, KeyError):
 position = custom_data_len
 custom_data_len += 1
 if "customdata" in result:
 result["customdata"] = np.hstack(
 (result["customdata"], g[col].values[:, None])
 if "customdata" in trace_patch:
 trace_patch["customdata"] = np.hstack(
 (
 trace_patch["customdata"],
 trace_data[col].values[:, None],
 )
 )
 else:
 result["customdata"] = g[col].values[:, None]
 v_label_col = get_decorated_label(args, col, None)
 mapping_labels[v_label_col] = "%%{customdata[%d]}" % (position)
 elif k == "color":
 trace_patch["customdata"] = trace_data[col].values[
 :, None
 ]
 attr_label_col = get_decorated_label(args, col, None)
 mapping_labels[attr_label_col] = "%%{customdata[%d]}" % (
 position
 )
 elif attr_name == "color":
 if trace_spec.constructor in [go.Choropleth, go.Choroplethmapbox]:
result["z"] = g[v]
result["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{z}"
trace_patch["z"] = trace_data[attr_value]
trace_patch["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{z}"
 elif trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
 if "marker" not in result:
result["marker"] = dict()
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()

 if args.get("color_is_continuous"):
result["marker"]["colors"] = g[v]
result["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{color}"
trace_patch["marker"]["colors"] = trace_data[attr_value]
trace_patch["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{color}"
 else:
result["marker"]["colors"] = []
trace_patch["marker"]["colors"] = []
 mapping = {}
 for cat in g[v]:
 for cat in trace_data[attr_value]:
 if mapping.get(cat) is None:
 mapping[cat] = args["color_discrete_sequence"][
 len(mapping) % len(args["color_discrete_sequence"])
 ]
result["marker"]["colors"].append(mapping[cat])
trace_patch["marker"]["colors"].append(mapping[cat])
 else:
 colorable = "marker"
 if trace_spec.constructor in [go.Parcats, go.Parcoords]:
 colorable = "line"
 if colorable not in result:
result[colorable] = dict()
result[colorable]["color"] = g[v]
result[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%%{%s.color}" % colorable
 elif k == "animation_group":
result["ids"] = g[v]
 elif k == "locations":
result[k] = g[v]
 mapping_labels[v_label] = "%{location}"
 elif k == "values":
result[k] = g[v]
 _label = "value" if v_label == "values" else v_label
 if colorable not in trace_patch:
trace_patch[colorable] = dict()
trace_patch[colorable]["color"] = trace_data[attr_value]
trace_patch[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%%{%s.color}" % colorable
 elif attr_name == "animation_group":
trace_patch["ids"] = trace_data[attr_value]
 elif attr_name == "locations":
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%{location}"
 elif attr_name == "values":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "value" if attr_label == "values" else attr_label
 mapping_labels[_label] = "%{value}"
 elif k == "parents":
result[k] = g[v]
 _label = "parent" if v_label == "parents" else v_label
 elif attr_name == "parents":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "parent" if attr_label == "parents" else attr_label
 mapping_labels[_label] = "%{parent}"
 elif k == "ids":
result[k] = g[v]
 _label = "id" if v_label == "ids" else v_label
 elif attr_name == "ids":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "id" if attr_label == "ids" else attr_label
 mapping_labels[_label] = "%{id}"
 elif k == "names":
 elif attr_name == "names":
 if trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
result["labels"] = g[v]
 _label = "label" if v_label == "names" else v_label
trace_patch["labels"] = trace_data[attr_value]
 _label = "label" if attr_label == "names" else attr_label
 mapping_labels[_label] = "%{label}"
 else:
result[k] = g[v]
trace_patch[attr_name] = trace_data[attr_value]
 else:
 if v:
result[k] = g[v]
 mapping_labels[v_label] = "%%{%s}" % k
 if attr_value:
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%%{%s}" % attr_name
 if trace_spec.constructor not in [
 go.Parcoords,
 go.Parcats,
 ]:
 hover_lines = [k + "=" + v for k, v in mapping_labels.items()]
result["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return result, fit_results
trace_patch["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return trace_patch, fit_results


def configure_axes(args, constructor, fig, orders):
Expand DownExpand Up@@ -1015,8 +1027,8 @@ def _check_dataframe_all_leaves(df):
 null_indices = np.nonzero(null_mask.any(axis=1).values)[0]
 for null_row_index in null_indices:
 row = null_mask.iloc[null_row_index]
indices = np.nonzero(row.values)[0]
 if not row[indices[0] :].all():
i = np.nonzero(row.values)[0][0]
 if not row[i:].all():
 raise ValueError(
 "None entries cannot have not-None children",
 df_sorted.iloc[null_row_index],
Expand DownExpand Up@@ -1058,6 +1070,7 @@ def process_dataframe_hierarchy(args):
 path = [new_col_name if x == col_name else x for x in path]
 df[new_col_name] = series_to_copy
 # ------------ Define aggregation functions --------------------------------

 def aggfunc_discrete(x):
 uniques = x.unique()
 if len(uniques) == 1:
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Strip utm_, fbclid, gclid, etc. from all links on page
(function() {
var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',
'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
function cleanUrl(url) {
try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
if (u.searchParams.has(p)) {
u.searchParams.delete(p);
changed = true;
}
});
return changed ? u.toString() : url;
} catch (e) {
return url;
}
}
function cleanLinks() {
document.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
cleanLinks();
var observer = new MutationObserver(function(mutations) {
mutations.forEach(function(m) {
m.addedNodes.forEach(function(node) {
if (node.nodeType === 1) {
if (node.tagName === 'A') cleanLinks();
node.querySelectorAll('a[href]').forEach(function(a) {
var clean = cleanUrl(a.href);
if (clean !== a.href) a.href = clean;
});
}
});
});
});
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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PX internals renaming#2135

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 Merged

nicolaskruchten
merged 6 commits into

from

Jan 31, 2020
 Merged


PX internals renaming
#2135
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d7fc1bc

tweaks to make flake8 happy


nicolaskruchten Jan 28, 2020
e9fa00d

g -> trace_data


nicolaskruchten Jan 28, 2020
ca87353

k -> attr_name


nicolaskruchten Jan 28, 2020
e7ced12

v -> attr_value


nicolaskruchten Jan 28, 2020
94303bc

v_label -> attr_label


nicolaskruchten Jan 28, 2020
95f78c2

result -> trace_patch


nicolaskruchten Jan 28, 2020

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207 changes: 110 additions & 97 deletions
packages/python/plotly/plotly/express/_core.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -137,7 +137,7 @@ def make_mapping(args, variable):
 )


def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
 """Populates a dict with arguments to update trace

 Parameters
Expand All@@ -147,7 +147,7 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 trace_spec : NamedTuple
 which kind of trace to be used (has constructor, marginal etc.
 attributes)
g : pandas DataFrame
trace_data : pandas DataFrame
 data
 mapping_labels : dict
 to be used for hovertemplate
Expand All@@ -156,87 +156,92 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):

 Returns
 -------
result : dict
trace_patch : dict
 dict to be used to update trace
 fit_results : dict
 fit information to be used for trendlines
 """
 if "line_close" in args and args["line_close"]:
g = g.append(g.iloc[0])
result = trace_spec.trace_patch.copy() or {}
trace_data = trace_data.append(trace_data.iloc[0])
trace_patch = trace_spec.trace_patch.copy() or {}
 fit_results = None
 hover_header = ""
 custom_data_len = 0
 for k in trace_spec.attrs:
v = args[k]
v_label = get_decorated_label(args, v, k)
 if k == "dimensions":
 for attr_name in trace_spec.attrs:
attr_value = args[attr_name]
attr_label = get_decorated_label(args, attr_value, attr_name)
 if attr_name == "dimensions":
 dims = [
 (name, column)
 for (name, column) in g.iteritems()
 if ((not v) or (name in v))
 for (name, column) in trace_data.iteritems()
 if ((not attr_value) or (name in attr_value))
 and (
 trace_spec.constructor != go.Parcoords
 or args["data_frame"][name].dtype.kind in "bifc"
 )
 and (
 trace_spec.constructor != go.Parcats
 or (v is not None and name in v)
 or (attr_value is not None and name in attr_value)
 or len(args["data_frame"][name].unique())
 <= args["dimensions_max_cardinality"]
 )
 ]
result["dimensions"] = [
trace_patch["dimensions"] = [
 dict(label=get_label(args, name), values=column.values)
 for (name, column) in dims
 ]
 if trace_spec.constructor == go.Splom:
 for d in result["dimensions"]:
 for d in trace_patch["dimensions"]:
 d["axis"] = dict(matches=True)
 mapping_labels["%{xaxis.title.text}"] = "%{x}"
 mapping_labels["%{yaxis.title.text}"] = "%{y}"

 elif (
v is not None
 or (trace_spec.constructor == go.Histogram and k in ["x", "y"])
attr_value is not None
 or (trace_spec.constructor == go.Histogram and attr_name in ["x", "y"])
 or (
 trace_spec.constructor in [go.Histogram2d, go.Histogram2dContour]
 and k == "z"
 and attr_name == "z"
 )
 ):
 if k == "size":
 if "marker" not in result:
result["marker"] = dict()
result["marker"]["size"] = g[v]
result["marker"]["sizemode"] = "area"
result["marker"]["sizeref"] = sizeref
 mapping_labels[v_label] = "%{marker.size}"
 elif k == "marginal_x":
 if attr_name == "size":
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()
trace_patch["marker"]["size"] = trace_data[attr_value]
trace_patch["marker"]["sizemode"] = "area"
trace_patch["marker"]["sizeref"] = sizeref
 mapping_labels[attr_label] = "%{marker.size}"
 elif attr_name == "marginal_x":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{y}"
 elif k == "marginal_y":
 elif attr_name == "marginal_y":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{x}"
 elif k == "trendline":
 if v in ["ols", "lowess"] and args["x"] and args["y"] and len(g) > 1:
 elif attr_name == "trendline":
 if (
 attr_value in ["ols", "lowess"]
 and args["x"]
 and args["y"]
 and len(trace_data) > 1
 ):
 import statsmodels.api as sm

 # sorting is bad but trace_specs with "trendline" have no other attrs
g2 = g.sort_values(by=args["x"])
 y = g2[args["y"]]
 x = g2[args["x"]]
result["x"] = x
sorted_trace_data = trace_data.sort_values(by=args["x"])
 y = sorted_trace_data[args["y"]]
 x = sorted_trace_data[args["x"]]
trace_patch["x"] = x

 if x.dtype.type == np.datetime64:
 x = x.astype(int) / 10 ** 9 # convert to unix epoch seconds

 if v == "lowess":
 if attr_value == "lowess":
 trendline = sm.nonparametric.lowess(y, x)
result["y"] = trendline[:, 1]
trace_patch["y"] = trendline[:, 1]
 hover_header = "<b>LOWESS trendline</b><br><br>"
 elif v == "ols":
 elif attr_value == "ols":
 fit_results = sm.OLS(y.values, sm.add_constant(x.values)).fit()
result["y"] = fit_results.predict()
trace_patch["y"] = fit_results.predict()
 hover_header = "<b>OLS trendline</b><br>"
 hover_header += "%s = %g * %s + %g<br>" % (
 args["y"],
Expand All@@ -250,120 +255,127 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 mapping_labels[get_label(args, args["x"])] = "%{x}"
 mapping_labels[get_label(args, args["y"])] = "%{y} <b>(trend)</b>"

 elif k.startswith("error"):
 error_xy = k[:7]
 arr = "arrayminus" if k.endswith("minus") else "array"
 if error_xy not in result:
result[error_xy] = {}
result[error_xy][arr] = g[v]
 elif k == "custom_data":
result["customdata"] = g[v].values
 custom_data_len = len(v) # number of custom data columns
 elif k == "hover_name":
 elif attr_name.startswith("error"):
 error_xy = attr_name[:7]
 arr = "arrayminus" if attr_name.endswith("minus") else "array"
 if error_xy not in trace_patch:
trace_patch[error_xy] = {}
trace_patch[error_xy][arr] = trace_data[attr_value]
 elif attr_name == "custom_data":
trace_patch["customdata"] = trace_data[attr_value].values
 custom_data_len = len(attr_value) # number of custom data columns
 elif attr_name == "hover_name":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
result["hovertext"] = g[v]
trace_patch["hovertext"] = trace_data[attr_value]
 if hover_header == "":
 hover_header = "<b>%{hovertext}</b><br><br>"
 elif k == "hover_data":
 elif attr_name == "hover_data":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
 for col in v:
 for col in attr_value:
 try:
 position = args["custom_data"].index(col)
 except (ValueError, AttributeError, KeyError):
 position = custom_data_len
 custom_data_len += 1
 if "customdata" in result:
 result["customdata"] = np.hstack(
 (result["customdata"], g[col].values[:, None])
 if "customdata" in trace_patch:
 trace_patch["customdata"] = np.hstack(
 (
 trace_patch["customdata"],
 trace_data[col].values[:, None],
 )
 )
 else:
 result["customdata"] = g[col].values[:, None]
 v_label_col = get_decorated_label(args, col, None)
 mapping_labels[v_label_col] = "%%{customdata[%d]}" % (position)
 elif k == "color":
 trace_patch["customdata"] = trace_data[col].values[
 :, None
 ]
 attr_label_col = get_decorated_label(args, col, None)
 mapping_labels[attr_label_col] = "%%{customdata[%d]}" % (
 position
 )
 elif attr_name == "color":
 if trace_spec.constructor in [go.Choropleth, go.Choroplethmapbox]:
result["z"] = g[v]
result["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{z}"
trace_patch["z"] = trace_data[attr_value]
trace_patch["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{z}"
 elif trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
 if "marker" not in result:
result["marker"] = dict()
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()

 if args.get("color_is_continuous"):
result["marker"]["colors"] = g[v]
result["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{color}"
trace_patch["marker"]["colors"] = trace_data[attr_value]
trace_patch["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{color}"
 else:
result["marker"]["colors"] = []
trace_patch["marker"]["colors"] = []
 mapping = {}
 for cat in g[v]:
 for cat in trace_data[attr_value]:
 if mapping.get(cat) is None:
 mapping[cat] = args["color_discrete_sequence"][
 len(mapping) % len(args["color_discrete_sequence"])
 ]
result["marker"]["colors"].append(mapping[cat])
trace_patch["marker"]["colors"].append(mapping[cat])
 else:
 colorable = "marker"
 if trace_spec.constructor in [go.Parcats, go.Parcoords]:
 colorable = "line"
 if colorable not in result:
result[colorable] = dict()
result[colorable]["color"] = g[v]
result[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%%{%s.color}" % colorable
 elif k == "animation_group":
result["ids"] = g[v]
 elif k == "locations":
result[k] = g[v]
 mapping_labels[v_label] = "%{location}"
 elif k == "values":
result[k] = g[v]
 _label = "value" if v_label == "values" else v_label
 if colorable not in trace_patch:
trace_patch[colorable] = dict()
trace_patch[colorable]["color"] = trace_data[attr_value]
trace_patch[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%%{%s.color}" % colorable
 elif attr_name == "animation_group":
trace_patch["ids"] = trace_data[attr_value]
 elif attr_name == "locations":
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%{location}"
 elif attr_name == "values":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "value" if attr_label == "values" else attr_label
 mapping_labels[_label] = "%{value}"
 elif k == "parents":
result[k] = g[v]
 _label = "parent" if v_label == "parents" else v_label
 elif attr_name == "parents":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "parent" if attr_label == "parents" else attr_label
 mapping_labels[_label] = "%{parent}"
 elif k == "ids":
result[k] = g[v]
 _label = "id" if v_label == "ids" else v_label
 elif attr_name == "ids":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "id" if attr_label == "ids" else attr_label
 mapping_labels[_label] = "%{id}"
 elif k == "names":
 elif attr_name == "names":
 if trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
result["labels"] = g[v]
 _label = "label" if v_label == "names" else v_label
trace_patch["labels"] = trace_data[attr_value]
 _label = "label" if attr_label == "names" else attr_label
 mapping_labels[_label] = "%{label}"
 else:
result[k] = g[v]
trace_patch[attr_name] = trace_data[attr_value]
 else:
 if v:
result[k] = g[v]
 mapping_labels[v_label] = "%%{%s}" % k
 if attr_value:
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%%{%s}" % attr_name
 if trace_spec.constructor not in [
 go.Parcoords,
 go.Parcats,
 ]:
 hover_lines = [k + "=" + v for k, v in mapping_labels.items()]
result["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return result, fit_results
trace_patch["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return trace_patch, fit_results


def configure_axes(args, constructor, fig, orders):
Expand DownExpand Up@@ -1015,8 +1027,8 @@ def _check_dataframe_all_leaves(df):
 null_indices = np.nonzero(null_mask.any(axis=1).values)[0]
 for null_row_index in null_indices:
 row = null_mask.iloc[null_row_index]
indices = np.nonzero(row.values)[0]
 if not row[indices[0] :].all():
i = np.nonzero(row.values)[0][0]
 if not row[i:].all():
 raise ValueError(
 "None entries cannot have not-None children",
 df_sorted.iloc[null_row_index],
Expand DownExpand Up@@ -1058,6 +1070,7 @@ def process_dataframe_hierarchy(args):
 path = [new_col_name if x == col_name else x for x in path]
 df[new_col_name] = series_to_copy
 # ------------ Define aggregation functions --------------------------------

 def aggfunc_discrete(x):
 uniques = x.unique()
 if len(uniques) == 1:
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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PX internals renaming#2135

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 Merged

nicolaskruchten
merged 6 commits into

from

Jan 31, 2020
 Merged


PX internals renaming
#2135
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d7fc1bc

tweaks to make flake8 happy


nicolaskruchten Jan 28, 2020
e9fa00d

g -> trace_data


nicolaskruchten Jan 28, 2020
ca87353

k -> attr_name


nicolaskruchten Jan 28, 2020
e7ced12

v -> attr_value


nicolaskruchten Jan 28, 2020
94303bc

v_label -> attr_label


nicolaskruchten Jan 28, 2020
95f78c2

result -> trace_patch


nicolaskruchten Jan 28, 2020

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207 changes: 110 additions & 97 deletions
packages/python/plotly/plotly/express/_core.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -137,7 +137,7 @@ def make_mapping(args, variable):
 )


def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
 """Populates a dict with arguments to update trace

 Parameters
Expand All@@ -147,7 +147,7 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 trace_spec : NamedTuple
 which kind of trace to be used (has constructor, marginal etc.
 attributes)
g : pandas DataFrame
trace_data : pandas DataFrame
 data
 mapping_labels : dict
 to be used for hovertemplate
Expand All@@ -156,87 +156,92 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):

 Returns
 -------
result : dict
trace_patch : dict
 dict to be used to update trace
 fit_results : dict
 fit information to be used for trendlines
 """
 if "line_close" in args and args["line_close"]:
g = g.append(g.iloc[0])
result = trace_spec.trace_patch.copy() or {}
trace_data = trace_data.append(trace_data.iloc[0])
trace_patch = trace_spec.trace_patch.copy() or {}
 fit_results = None
 hover_header = ""
 custom_data_len = 0
 for k in trace_spec.attrs:
v = args[k]
v_label = get_decorated_label(args, v, k)
 if k == "dimensions":
 for attr_name in trace_spec.attrs:
attr_value = args[attr_name]
attr_label = get_decorated_label(args, attr_value, attr_name)
 if attr_name == "dimensions":
 dims = [
 (name, column)
 for (name, column) in g.iteritems()
 if ((not v) or (name in v))
 for (name, column) in trace_data.iteritems()
 if ((not attr_value) or (name in attr_value))
 and (
 trace_spec.constructor != go.Parcoords
 or args["data_frame"][name].dtype.kind in "bifc"
 )
 and (
 trace_spec.constructor != go.Parcats
 or (v is not None and name in v)
 or (attr_value is not None and name in attr_value)
 or len(args["data_frame"][name].unique())
 <= args["dimensions_max_cardinality"]
 )
 ]
result["dimensions"] = [
trace_patch["dimensions"] = [
 dict(label=get_label(args, name), values=column.values)
 for (name, column) in dims
 ]
 if trace_spec.constructor == go.Splom:
 for d in result["dimensions"]:
 for d in trace_patch["dimensions"]:
 d["axis"] = dict(matches=True)
 mapping_labels["%{xaxis.title.text}"] = "%{x}"
 mapping_labels["%{yaxis.title.text}"] = "%{y}"

 elif (
v is not None
 or (trace_spec.constructor == go.Histogram and k in ["x", "y"])
attr_value is not None
 or (trace_spec.constructor == go.Histogram and attr_name in ["x", "y"])
 or (
 trace_spec.constructor in [go.Histogram2d, go.Histogram2dContour]
 and k == "z"
 and attr_name == "z"
 )
 ):
 if k == "size":
 if "marker" not in result:
result["marker"] = dict()
result["marker"]["size"] = g[v]
result["marker"]["sizemode"] = "area"
result["marker"]["sizeref"] = sizeref
 mapping_labels[v_label] = "%{marker.size}"
 elif k == "marginal_x":
 if attr_name == "size":
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()
trace_patch["marker"]["size"] = trace_data[attr_value]
trace_patch["marker"]["sizemode"] = "area"
trace_patch["marker"]["sizeref"] = sizeref
 mapping_labels[attr_label] = "%{marker.size}"
 elif attr_name == "marginal_x":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{y}"
 elif k == "marginal_y":
 elif attr_name == "marginal_y":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{x}"
 elif k == "trendline":
 if v in ["ols", "lowess"] and args["x"] and args["y"] and len(g) > 1:
 elif attr_name == "trendline":
 if (
 attr_value in ["ols", "lowess"]
 and args["x"]
 and args["y"]
 and len(trace_data) > 1
 ):
 import statsmodels.api as sm

 # sorting is bad but trace_specs with "trendline" have no other attrs
g2 = g.sort_values(by=args["x"])
 y = g2[args["y"]]
 x = g2[args["x"]]
result["x"] = x
sorted_trace_data = trace_data.sort_values(by=args["x"])
 y = sorted_trace_data[args["y"]]
 x = sorted_trace_data[args["x"]]
trace_patch["x"] = x

 if x.dtype.type == np.datetime64:
 x = x.astype(int) / 10 ** 9 # convert to unix epoch seconds

 if v == "lowess":
 if attr_value == "lowess":
 trendline = sm.nonparametric.lowess(y, x)
result["y"] = trendline[:, 1]
trace_patch["y"] = trendline[:, 1]
 hover_header = "<b>LOWESS trendline</b><br><br>"
 elif v == "ols":
 elif attr_value == "ols":
 fit_results = sm.OLS(y.values, sm.add_constant(x.values)).fit()
result["y"] = fit_results.predict()
trace_patch["y"] = fit_results.predict()
 hover_header = "<b>OLS trendline</b><br>"
 hover_header += "%s = %g * %s + %g<br>" % (
 args["y"],
Expand All@@ -250,120 +255,127 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 mapping_labels[get_label(args, args["x"])] = "%{x}"
 mapping_labels[get_label(args, args["y"])] = "%{y} <b>(trend)</b>"

 elif k.startswith("error"):
 error_xy = k[:7]
 arr = "arrayminus" if k.endswith("minus") else "array"
 if error_xy not in result:
result[error_xy] = {}
result[error_xy][arr] = g[v]
 elif k == "custom_data":
result["customdata"] = g[v].values
 custom_data_len = len(v) # number of custom data columns
 elif k == "hover_name":
 elif attr_name.startswith("error"):
 error_xy = attr_name[:7]
 arr = "arrayminus" if attr_name.endswith("minus") else "array"
 if error_xy not in trace_patch:
trace_patch[error_xy] = {}
trace_patch[error_xy][arr] = trace_data[attr_value]
 elif attr_name == "custom_data":
trace_patch["customdata"] = trace_data[attr_value].values
 custom_data_len = len(attr_value) # number of custom data columns
 elif attr_name == "hover_name":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
result["hovertext"] = g[v]
trace_patch["hovertext"] = trace_data[attr_value]
 if hover_header == "":
 hover_header = "<b>%{hovertext}</b><br><br>"
 elif k == "hover_data":
 elif attr_name == "hover_data":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
 for col in v:
 for col in attr_value:
 try:
 position = args["custom_data"].index(col)
 except (ValueError, AttributeError, KeyError):
 position = custom_data_len
 custom_data_len += 1
 if "customdata" in result:
 result["customdata"] = np.hstack(
 (result["customdata"], g[col].values[:, None])
 if "customdata" in trace_patch:
 trace_patch["customdata"] = np.hstack(
 (
 trace_patch["customdata"],
 trace_data[col].values[:, None],
 )
 )
 else:
 result["customdata"] = g[col].values[:, None]
 v_label_col = get_decorated_label(args, col, None)
 mapping_labels[v_label_col] = "%%{customdata[%d]}" % (position)
 elif k == "color":
 trace_patch["customdata"] = trace_data[col].values[
 :, None
 ]
 attr_label_col = get_decorated_label(args, col, None)
 mapping_labels[attr_label_col] = "%%{customdata[%d]}" % (
 position
 )
 elif attr_name == "color":
 if trace_spec.constructor in [go.Choropleth, go.Choroplethmapbox]:
result["z"] = g[v]
result["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{z}"
trace_patch["z"] = trace_data[attr_value]
trace_patch["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{z}"
 elif trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
 if "marker" not in result:
result["marker"] = dict()
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()

 if args.get("color_is_continuous"):
result["marker"]["colors"] = g[v]
result["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{color}"
trace_patch["marker"]["colors"] = trace_data[attr_value]
trace_patch["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{color}"
 else:
result["marker"]["colors"] = []
trace_patch["marker"]["colors"] = []
 mapping = {}
 for cat in g[v]:
 for cat in trace_data[attr_value]:
 if mapping.get(cat) is None:
 mapping[cat] = args["color_discrete_sequence"][
 len(mapping) % len(args["color_discrete_sequence"])
 ]
result["marker"]["colors"].append(mapping[cat])
trace_patch["marker"]["colors"].append(mapping[cat])
 else:
 colorable = "marker"
 if trace_spec.constructor in [go.Parcats, go.Parcoords]:
 colorable = "line"
 if colorable not in result:
result[colorable] = dict()
result[colorable]["color"] = g[v]
result[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%%{%s.color}" % colorable
 elif k == "animation_group":
result["ids"] = g[v]
 elif k == "locations":
result[k] = g[v]
 mapping_labels[v_label] = "%{location}"
 elif k == "values":
result[k] = g[v]
 _label = "value" if v_label == "values" else v_label
 if colorable not in trace_patch:
trace_patch[colorable] = dict()
trace_patch[colorable]["color"] = trace_data[attr_value]
trace_patch[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%%{%s.color}" % colorable
 elif attr_name == "animation_group":
trace_patch["ids"] = trace_data[attr_value]
 elif attr_name == "locations":
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%{location}"
 elif attr_name == "values":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "value" if attr_label == "values" else attr_label
 mapping_labels[_label] = "%{value}"
 elif k == "parents":
result[k] = g[v]
 _label = "parent" if v_label == "parents" else v_label
 elif attr_name == "parents":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "parent" if attr_label == "parents" else attr_label
 mapping_labels[_label] = "%{parent}"
 elif k == "ids":
result[k] = g[v]
 _label = "id" if v_label == "ids" else v_label
 elif attr_name == "ids":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "id" if attr_label == "ids" else attr_label
 mapping_labels[_label] = "%{id}"
 elif k == "names":
 elif attr_name == "names":
 if trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
result["labels"] = g[v]
 _label = "label" if v_label == "names" else v_label
trace_patch["labels"] = trace_data[attr_value]
 _label = "label" if attr_label == "names" else attr_label
 mapping_labels[_label] = "%{label}"
 else:
result[k] = g[v]
trace_patch[attr_name] = trace_data[attr_value]
 else:
 if v:
result[k] = g[v]
 mapping_labels[v_label] = "%%{%s}" % k
 if attr_value:
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%%{%s}" % attr_name
 if trace_spec.constructor not in [
 go.Parcoords,
 go.Parcats,
 ]:
 hover_lines = [k + "=" + v for k, v in mapping_labels.items()]
result["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return result, fit_results
trace_patch["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return trace_patch, fit_results


def configure_axes(args, constructor, fig, orders):
Expand DownExpand Up@@ -1015,8 +1027,8 @@ def _check_dataframe_all_leaves(df):
 null_indices = np.nonzero(null_mask.any(axis=1).values)[0]
 for null_row_index in null_indices:
 row = null_mask.iloc[null_row_index]
indices = np.nonzero(row.values)[0]
 if not row[indices[0] :].all():
i = np.nonzero(row.values)[0][0]
 if not row[i:].all():
 raise ValueError(
 "None entries cannot have not-None children",
 df_sorted.iloc[null_row_index],
Expand DownExpand Up@@ -1058,6 +1070,7 @@ def process_dataframe_hierarchy(args):
 path = [new_col_name if x == col_name else x for x in path]
 df[new_col_name] = series_to_copy
 # ------------ Define aggregation functions --------------------------------

 def aggfunc_discrete(x):
 uniques = x.unique()
 if len(uniques) == 1:
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
PX internals renaming#2135

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 Merged

nicolaskruchten
merged 6 commits into

from

Jan 31, 2020
 Merged


PX internals renaming
#2135
 Changes from all commits
Commits

Show all changes


6 commits


Select commit
Hold shift + click to select a range
d7fc1bc

tweaks to make flake8 happy


nicolaskruchten Jan 28, 2020
e9fa00d

g -> trace_data


nicolaskruchten Jan 28, 2020
ca87353

k -> attr_name


nicolaskruchten Jan 28, 2020
e7ced12

v -> attr_value


nicolaskruchten Jan 28, 2020
94303bc

v_label -> attr_label


nicolaskruchten Jan 28, 2020
95f78c2

result -> trace_patch


nicolaskruchten Jan 28, 2020

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207 changes: 110 additions & 97 deletions
packages/python/plotly/plotly/express/_core.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -137,7 +137,7 @@ def make_mapping(args, variable):
 )


def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
 """Populates a dict with arguments to update trace

 Parameters
Expand All@@ -147,7 +147,7 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 trace_spec : NamedTuple
 which kind of trace to be used (has constructor, marginal etc.
 attributes)
g : pandas DataFrame
trace_data : pandas DataFrame
 data
 mapping_labels : dict
 to be used for hovertemplate
Expand All@@ -156,87 +156,92 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):

 Returns
 -------
result : dict
trace_patch : dict
 dict to be used to update trace
 fit_results : dict
 fit information to be used for trendlines
 """
 if "line_close" in args and args["line_close"]:
g = g.append(g.iloc[0])
result = trace_spec.trace_patch.copy() or {}
trace_data = trace_data.append(trace_data.iloc[0])
trace_patch = trace_spec.trace_patch.copy() or {}
 fit_results = None
 hover_header = ""
 custom_data_len = 0
 for k in trace_spec.attrs:
v = args[k]
v_label = get_decorated_label(args, v, k)
 if k == "dimensions":
 for attr_name in trace_spec.attrs:
attr_value = args[attr_name]
attr_label = get_decorated_label(args, attr_value, attr_name)
 if attr_name == "dimensions":
 dims = [
 (name, column)
 for (name, column) in g.iteritems()
 if ((not v) or (name in v))
 for (name, column) in trace_data.iteritems()
 if ((not attr_value) or (name in attr_value))
 and (
 trace_spec.constructor != go.Parcoords
 or args["data_frame"][name].dtype.kind in "bifc"
 )
 and (
 trace_spec.constructor != go.Parcats
 or (v is not None and name in v)
 or (attr_value is not None and name in attr_value)
 or len(args["data_frame"][name].unique())
 <= args["dimensions_max_cardinality"]
 )
 ]
result["dimensions"] = [
trace_patch["dimensions"] = [
 dict(label=get_label(args, name), values=column.values)
 for (name, column) in dims
 ]
 if trace_spec.constructor == go.Splom:
 for d in result["dimensions"]:
 for d in trace_patch["dimensions"]:
 d["axis"] = dict(matches=True)
 mapping_labels["%{xaxis.title.text}"] = "%{x}"
 mapping_labels["%{yaxis.title.text}"] = "%{y}"

 elif (
v is not None
 or (trace_spec.constructor == go.Histogram and k in ["x", "y"])
attr_value is not None
 or (trace_spec.constructor == go.Histogram and attr_name in ["x", "y"])
 or (
 trace_spec.constructor in [go.Histogram2d, go.Histogram2dContour]
 and k == "z"
 and attr_name == "z"
 )
 ):
 if k == "size":
 if "marker" not in result:
result["marker"] = dict()
result["marker"]["size"] = g[v]
result["marker"]["sizemode"] = "area"
result["marker"]["sizeref"] = sizeref
 mapping_labels[v_label] = "%{marker.size}"
 elif k == "marginal_x":
 if attr_name == "size":
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()
trace_patch["marker"]["size"] = trace_data[attr_value]
trace_patch["marker"]["sizemode"] = "area"
trace_patch["marker"]["sizeref"] = sizeref
 mapping_labels[attr_label] = "%{marker.size}"
 elif attr_name == "marginal_x":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{y}"
 elif k == "marginal_y":
 elif attr_name == "marginal_y":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{x}"
 elif k == "trendline":
 if v in ["ols", "lowess"] and args["x"] and args["y"] and len(g) > 1:
 elif attr_name == "trendline":
 if (
 attr_value in ["ols", "lowess"]
 and args["x"]
 and args["y"]
 and len(trace_data) > 1
 ):
 import statsmodels.api as sm

 # sorting is bad but trace_specs with "trendline" have no other attrs
g2 = g.sort_values(by=args["x"])
 y = g2[args["y"]]
 x = g2[args["x"]]
result["x"] = x
sorted_trace_data = trace_data.sort_values(by=args["x"])
 y = sorted_trace_data[args["y"]]
 x = sorted_trace_data[args["x"]]
trace_patch["x"] = x

 if x.dtype.type == np.datetime64:
 x = x.astype(int) / 10 ** 9 # convert to unix epoch seconds

 if v == "lowess":
 if attr_value == "lowess":
 trendline = sm.nonparametric.lowess(y, x)
result["y"] = trendline[:, 1]
trace_patch["y"] = trendline[:, 1]
 hover_header = "<b>LOWESS trendline</b><br><br>"
 elif v == "ols":
 elif attr_value == "ols":
 fit_results = sm.OLS(y.values, sm.add_constant(x.values)).fit()
result["y"] = fit_results.predict()
trace_patch["y"] = fit_results.predict()
 hover_header = "<b>OLS trendline</b><br>"
 hover_header += "%s = %g * %s + %g<br>" % (
 args["y"],
Expand All@@ -250,120 +255,127 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 mapping_labels[get_label(args, args["x"])] = "%{x}"
 mapping_labels[get_label(args, args["y"])] = "%{y} <b>(trend)</b>"

 elif k.startswith("error"):
 error_xy = k[:7]
 arr = "arrayminus" if k.endswith("minus") else "array"
 if error_xy not in result:
result[error_xy] = {}
result[error_xy][arr] = g[v]
 elif k == "custom_data":
result["customdata"] = g[v].values
 custom_data_len = len(v) # number of custom data columns
 elif k == "hover_name":
 elif attr_name.startswith("error"):
 error_xy = attr_name[:7]
 arr = "arrayminus" if attr_name.endswith("minus") else "array"
 if error_xy not in trace_patch:
trace_patch[error_xy] = {}
trace_patch[error_xy][arr] = trace_data[attr_value]
 elif attr_name == "custom_data":
trace_patch["customdata"] = trace_data[attr_value].values
 custom_data_len = len(attr_value) # number of custom data columns
 elif attr_name == "hover_name":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
result["hovertext"] = g[v]
trace_patch["hovertext"] = trace_data[attr_value]
 if hover_header == "":
 hover_header = "<b>%{hovertext}</b><br><br>"
 elif k == "hover_data":
 elif attr_name == "hover_data":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
 for col in v:
 for col in attr_value:
 try:
 position = args["custom_data"].index(col)
 except (ValueError, AttributeError, KeyError):
 position = custom_data_len
 custom_data_len += 1
 if "customdata" in result:
 result["customdata"] = np.hstack(
 (result["customdata"], g[col].values[:, None])
 if "customdata" in trace_patch:
 trace_patch["customdata"] = np.hstack(
 (
 trace_patch["customdata"],
 trace_data[col].values[:, None],
 )
 )
 else:
 result["customdata"] = g[col].values[:, None]
 v_label_col = get_decorated_label(args, col, None)
 mapping_labels[v_label_col] = "%%{customdata[%d]}" % (position)
 elif k == "color":
 trace_patch["customdata"] = trace_data[col].values[
 :, None
 ]
 attr_label_col = get_decorated_label(args, col, None)
 mapping_labels[attr_label_col] = "%%{customdata[%d]}" % (
 position
 )
 elif attr_name == "color":
 if trace_spec.constructor in [go.Choropleth, go.Choroplethmapbox]:
result["z"] = g[v]
result["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{z}"
trace_patch["z"] = trace_data[attr_value]
trace_patch["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{z}"
 elif trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
 if "marker" not in result:
result["marker"] = dict()
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()

 if args.get("color_is_continuous"):
result["marker"]["colors"] = g[v]
result["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{color}"
trace_patch["marker"]["colors"] = trace_data[attr_value]
trace_patch["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{color}"
 else:
result["marker"]["colors"] = []
trace_patch["marker"]["colors"] = []
 mapping = {}
 for cat in g[v]:
 for cat in trace_data[attr_value]:
 if mapping.get(cat) is None:
 mapping[cat] = args["color_discrete_sequence"][
 len(mapping) % len(args["color_discrete_sequence"])
 ]
result["marker"]["colors"].append(mapping[cat])
trace_patch["marker"]["colors"].append(mapping[cat])
 else:
 colorable = "marker"
 if trace_spec.constructor in [go.Parcats, go.Parcoords]:
 colorable = "line"
 if colorable not in result:
result[colorable] = dict()
result[colorable]["color"] = g[v]
result[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%%{%s.color}" % colorable
 elif k == "animation_group":
result["ids"] = g[v]
 elif k == "locations":
result[k] = g[v]
 mapping_labels[v_label] = "%{location}"
 elif k == "values":
result[k] = g[v]
 _label = "value" if v_label == "values" else v_label
 if colorable not in trace_patch:
trace_patch[colorable] = dict()
trace_patch[colorable]["color"] = trace_data[attr_value]
trace_patch[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%%{%s.color}" % colorable
 elif attr_name == "animation_group":
trace_patch["ids"] = trace_data[attr_value]
 elif attr_name == "locations":
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%{location}"
 elif attr_name == "values":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "value" if attr_label == "values" else attr_label
 mapping_labels[_label] = "%{value}"
 elif k == "parents":
result[k] = g[v]
 _label = "parent" if v_label == "parents" else v_label
 elif attr_name == "parents":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "parent" if attr_label == "parents" else attr_label
 mapping_labels[_label] = "%{parent}"
 elif k == "ids":
result[k] = g[v]
 _label = "id" if v_label == "ids" else v_label
 elif attr_name == "ids":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "id" if attr_label == "ids" else attr_label
 mapping_labels[_label] = "%{id}"
 elif k == "names":
 elif attr_name == "names":
 if trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
result["labels"] = g[v]
 _label = "label" if v_label == "names" else v_label
trace_patch["labels"] = trace_data[attr_value]
 _label = "label" if attr_label == "names" else attr_label
 mapping_labels[_label] = "%{label}"
 else:
result[k] = g[v]
trace_patch[attr_name] = trace_data[attr_value]
 else:
 if v:
result[k] = g[v]
 mapping_labels[v_label] = "%%{%s}" % k
 if attr_value:
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%%{%s}" % attr_name
 if trace_spec.constructor not in [
 go.Parcoords,
 go.Parcats,
 ]:
 hover_lines = [k + "=" + v for k, v in mapping_labels.items()]
result["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return result, fit_results
trace_patch["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return trace_patch, fit_results


def configure_axes(args, constructor, fig, orders):
Expand DownExpand Up@@ -1015,8 +1027,8 @@ def _check_dataframe_all_leaves(df):
 null_indices = np.nonzero(null_mask.any(axis=1).values)[0]
 for null_row_index in null_indices:
 row = null_mask.iloc[null_row_index]
indices = np.nonzero(row.values)[0]
 if not row[indices[0] :].all():
i = np.nonzero(row.values)[0][0]
 if not row[i:].all():
 raise ValueError(
 "None entries cannot have not-None children",
 df_sorted.iloc[null_row_index],
Expand DownExpand Up@@ -1058,6 +1070,7 @@ def process_dataframe_hierarchy(args):
 path = [new_col_name if x == col_name else x for x in path]
 df[new_col_name] = series_to_copy
 # ------------ Define aggregation functions --------------------------------

 def aggfunc_discrete(x):
 uniques = x.unique()
 if len(uniques) == 1:
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Universal Dark Mode - works on any site
(function() {
var enabled = true;
function applyDarkMode() {
if (!enabled) return;
// Create style element if it doesn't exist
var style = document.getElementById('universal-dark-mode-style');
if (!style) {
style = document.createElement('style');
style.id = 'universal-dark-mode-style';
document.head.appendChild(style);
}
// Dark mode CSS - inverts colors but preserves images/video
style.textContent = '
/* Invert everything except media */
html {
filter: invert(1) hue-rotate(180deg) !important;
background: #1a1a2e !important;
}
/* Restore images, videos, iframes, canvas */
img, video, iframe, canvas, svg, picture, [style*="background-image"] {
filter: invert(1) hue-rotate(180deg) !important;
}
/* Preserve specific elements that should not be inverted */
.no-dark-mode, .no-dark-mode *,
[data-theme="light"], [data-theme="light"],
.ace_editor, .ace_editor *,
.CodeMirror, .CodeMirror *,
.monaco-editor, .monaco-editor *,
.markdown-body pre, .markdown-body pre *,
.highlight, .highlight *,
pre code, pre code * {
filter: none !important;
}
/* Fix common UI elements */
.modal, .popup, .dropdown-menu, .tooltip, .popover {
filter: invert(1) hue-rotate(180deg) !important;
background: #2d2d44 !important;
border-color: #444 !important;
}
/* Scrollbars */
::-webkit-scrollbar { background: #1a1a2e !important; }
::-webkit-scrollbar-thumb { background: #444 !important; }
::-webkit-scrollbar-thumb:hover { background: #555 !important; }
/* Selection */
::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }
';
}
function removeDarkMode() {
var style = document.getElementById('universal-dark-mode-style');
if (style) style.remove();
}
// Toggle with Alt+Shift+D
document.addEventListener('keydown', function(e) {
if (e.altKey && e.shiftKey && e.key === 'D') {
e.preventDefault();
enabled = !enabled;
if (enabled) {
applyDarkMode();
console.log('[Universal Dark Mode] Enabled');
} else {
removeDarkMode();
console.log('[Universal Dark Mode] Disabled');
}
}
});
// Apply on load
applyDarkMode();
// Re-apply on dynamic content
var observer = new MutationObserver(function(mutations) {
if (enabled && !document.getElementById('universal-dark-mode-style')) {
applyDarkMode();
}
});
observer.observe(document.head, { childList: true });
console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');
})();
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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PX internals renaming#2135

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 Merged

nicolaskruchten
merged 6 commits into

from

Jan 31, 2020
 Merged


PX internals renaming
#2135
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d7fc1bc

tweaks to make flake8 happy


nicolaskruchten Jan 28, 2020
e9fa00d

g -> trace_data


nicolaskruchten Jan 28, 2020
ca87353

k -> attr_name


nicolaskruchten Jan 28, 2020
e7ced12

v -> attr_value


nicolaskruchten Jan 28, 2020
94303bc

v_label -> attr_label


nicolaskruchten Jan 28, 2020
95f78c2

result -> trace_patch


nicolaskruchten Jan 28, 2020

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207 changes: 110 additions & 97 deletions
packages/python/plotly/plotly/express/_core.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -137,7 +137,7 @@ def make_mapping(args, variable):
 )


def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref):
 """Populates a dict with arguments to update trace

 Parameters
Expand All@@ -147,7 +147,7 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 trace_spec : NamedTuple
 which kind of trace to be used (has constructor, marginal etc.
 attributes)
g : pandas DataFrame
trace_data : pandas DataFrame
 data
 mapping_labels : dict
 to be used for hovertemplate
Expand All@@ -156,87 +156,92 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):

 Returns
 -------
result : dict
trace_patch : dict
 dict to be used to update trace
 fit_results : dict
 fit information to be used for trendlines
 """
 if "line_close" in args and args["line_close"]:
g = g.append(g.iloc[0])
result = trace_spec.trace_patch.copy() or {}
trace_data = trace_data.append(trace_data.iloc[0])
trace_patch = trace_spec.trace_patch.copy() or {}
 fit_results = None
 hover_header = ""
 custom_data_len = 0
 for k in trace_spec.attrs:
v = args[k]
v_label = get_decorated_label(args, v, k)
 if k == "dimensions":
 for attr_name in trace_spec.attrs:
attr_value = args[attr_name]
attr_label = get_decorated_label(args, attr_value, attr_name)
 if attr_name == "dimensions":
 dims = [
 (name, column)
 for (name, column) in g.iteritems()
 if ((not v) or (name in v))
 for (name, column) in trace_data.iteritems()
 if ((not attr_value) or (name in attr_value))
 and (
 trace_spec.constructor != go.Parcoords
 or args["data_frame"][name].dtype.kind in "bifc"
 )
 and (
 trace_spec.constructor != go.Parcats
 or (v is not None and name in v)
 or (attr_value is not None and name in attr_value)
 or len(args["data_frame"][name].unique())
 <= args["dimensions_max_cardinality"]
 )
 ]
result["dimensions"] = [
trace_patch["dimensions"] = [
 dict(label=get_label(args, name), values=column.values)
 for (name, column) in dims
 ]
 if trace_spec.constructor == go.Splom:
 for d in result["dimensions"]:
 for d in trace_patch["dimensions"]:
 d["axis"] = dict(matches=True)
 mapping_labels["%{xaxis.title.text}"] = "%{x}"
 mapping_labels["%{yaxis.title.text}"] = "%{y}"

 elif (
v is not None
 or (trace_spec.constructor == go.Histogram and k in ["x", "y"])
attr_value is not None
 or (trace_spec.constructor == go.Histogram and attr_name in ["x", "y"])
 or (
 trace_spec.constructor in [go.Histogram2d, go.Histogram2dContour]
 and k == "z"
 and attr_name == "z"
 )
 ):
 if k == "size":
 if "marker" not in result:
result["marker"] = dict()
result["marker"]["size"] = g[v]
result["marker"]["sizemode"] = "area"
result["marker"]["sizeref"] = sizeref
 mapping_labels[v_label] = "%{marker.size}"
 elif k == "marginal_x":
 if attr_name == "size":
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()
trace_patch["marker"]["size"] = trace_data[attr_value]
trace_patch["marker"]["sizemode"] = "area"
trace_patch["marker"]["sizeref"] = sizeref
 mapping_labels[attr_label] = "%{marker.size}"
 elif attr_name == "marginal_x":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{y}"
 elif k == "marginal_y":
 elif attr_name == "marginal_y":
 if trace_spec.constructor == go.Histogram:
 mapping_labels["count"] = "%{x}"
 elif k == "trendline":
 if v in ["ols", "lowess"] and args["x"] and args["y"] and len(g) > 1:
 elif attr_name == "trendline":
 if (
 attr_value in ["ols", "lowess"]
 and args["x"]
 and args["y"]
 and len(trace_data) > 1
 ):
 import statsmodels.api as sm

 # sorting is bad but trace_specs with "trendline" have no other attrs
g2 = g.sort_values(by=args["x"])
 y = g2[args["y"]]
 x = g2[args["x"]]
result["x"] = x
sorted_trace_data = trace_data.sort_values(by=args["x"])
 y = sorted_trace_data[args["y"]]
 x = sorted_trace_data[args["x"]]
trace_patch["x"] = x

 if x.dtype.type == np.datetime64:
 x = x.astype(int) / 10 ** 9 # convert to unix epoch seconds

 if v == "lowess":
 if attr_value == "lowess":
 trendline = sm.nonparametric.lowess(y, x)
result["y"] = trendline[:, 1]
trace_patch["y"] = trendline[:, 1]
 hover_header = "<b>LOWESS trendline</b><br><br>"
 elif v == "ols":
 elif attr_value == "ols":
 fit_results = sm.OLS(y.values, sm.add_constant(x.values)).fit()
result["y"] = fit_results.predict()
trace_patch["y"] = fit_results.predict()
 hover_header = "<b>OLS trendline</b><br>"
 hover_header += "%s = %g * %s + %g<br>" % (
 args["y"],
Expand All@@ -250,120 +255,127 @@ def make_trace_kwargs(args, trace_spec, g, mapping_labels, sizeref):
 mapping_labels[get_label(args, args["x"])] = "%{x}"
 mapping_labels[get_label(args, args["y"])] = "%{y} <b>(trend)</b>"

 elif k.startswith("error"):
 error_xy = k[:7]
 arr = "arrayminus" if k.endswith("minus") else "array"
 if error_xy not in result:
result[error_xy] = {}
result[error_xy][arr] = g[v]
 elif k == "custom_data":
result["customdata"] = g[v].values
 custom_data_len = len(v) # number of custom data columns
 elif k == "hover_name":
 elif attr_name.startswith("error"):
 error_xy = attr_name[:7]
 arr = "arrayminus" if attr_name.endswith("minus") else "array"
 if error_xy not in trace_patch:
trace_patch[error_xy] = {}
trace_patch[error_xy][arr] = trace_data[attr_value]
 elif attr_name == "custom_data":
trace_patch["customdata"] = trace_data[attr_value].values
 custom_data_len = len(attr_value) # number of custom data columns
 elif attr_name == "hover_name":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
result["hovertext"] = g[v]
trace_patch["hovertext"] = trace_data[attr_value]
 if hover_header == "":
 hover_header = "<b>%{hovertext}</b><br><br>"
 elif k == "hover_data":
 elif attr_name == "hover_data":
 if trace_spec.constructor not in [
 go.Histogram,
 go.Histogram2d,
 go.Histogram2dContour,
 ]:
 for col in v:
 for col in attr_value:
 try:
 position = args["custom_data"].index(col)
 except (ValueError, AttributeError, KeyError):
 position = custom_data_len
 custom_data_len += 1
 if "customdata" in result:
 result["customdata"] = np.hstack(
 (result["customdata"], g[col].values[:, None])
 if "customdata" in trace_patch:
 trace_patch["customdata"] = np.hstack(
 (
 trace_patch["customdata"],
 trace_data[col].values[:, None],
 )
 )
 else:
 result["customdata"] = g[col].values[:, None]
 v_label_col = get_decorated_label(args, col, None)
 mapping_labels[v_label_col] = "%%{customdata[%d]}" % (position)
 elif k == "color":
 trace_patch["customdata"] = trace_data[col].values[
 :, None
 ]
 attr_label_col = get_decorated_label(args, col, None)
 mapping_labels[attr_label_col] = "%%{customdata[%d]}" % (
 position
 )
 elif attr_name == "color":
 if trace_spec.constructor in [go.Choropleth, go.Choroplethmapbox]:
result["z"] = g[v]
result["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{z}"
trace_patch["z"] = trace_data[attr_value]
trace_patch["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{z}"
 elif trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
 if "marker" not in result:
result["marker"] = dict()
 if "marker" not in trace_patch:
trace_patch["marker"] = dict()

 if args.get("color_is_continuous"):
result["marker"]["colors"] = g[v]
result["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%{color}"
trace_patch["marker"]["colors"] = trace_data[attr_value]
trace_patch["marker"]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%{color}"
 else:
result["marker"]["colors"] = []
trace_patch["marker"]["colors"] = []
 mapping = {}
 for cat in g[v]:
 for cat in trace_data[attr_value]:
 if mapping.get(cat) is None:
 mapping[cat] = args["color_discrete_sequence"][
 len(mapping) % len(args["color_discrete_sequence"])
 ]
result["marker"]["colors"].append(mapping[cat])
trace_patch["marker"]["colors"].append(mapping[cat])
 else:
 colorable = "marker"
 if trace_spec.constructor in [go.Parcats, go.Parcoords]:
 colorable = "line"
 if colorable not in result:
result[colorable] = dict()
result[colorable]["color"] = g[v]
result[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[v_label] = "%%{%s.color}" % colorable
 elif k == "animation_group":
result["ids"] = g[v]
 elif k == "locations":
result[k] = g[v]
 mapping_labels[v_label] = "%{location}"
 elif k == "values":
result[k] = g[v]
 _label = "value" if v_label == "values" else v_label
 if colorable not in trace_patch:
trace_patch[colorable] = dict()
trace_patch[colorable]["color"] = trace_data[attr_value]
trace_patch[colorable]["coloraxis"] = "coloraxis1"
 mapping_labels[attr_label] = "%%{%s.color}" % colorable
 elif attr_name == "animation_group":
trace_patch["ids"] = trace_data[attr_value]
 elif attr_name == "locations":
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%{location}"
 elif attr_name == "values":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "value" if attr_label == "values" else attr_label
 mapping_labels[_label] = "%{value}"
 elif k == "parents":
result[k] = g[v]
 _label = "parent" if v_label == "parents" else v_label
 elif attr_name == "parents":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "parent" if attr_label == "parents" else attr_label
 mapping_labels[_label] = "%{parent}"
 elif k == "ids":
result[k] = g[v]
 _label = "id" if v_label == "ids" else v_label
 elif attr_name == "ids":
trace_patch[attr_name] = trace_data[attr_value]
 _label = "id" if attr_label == "ids" else attr_label
 mapping_labels[_label] = "%{id}"
 elif k == "names":
 elif attr_name == "names":
 if trace_spec.constructor in [
 go.Sunburst,
 go.Treemap,
 go.Pie,
 go.Funnelarea,
 ]:
result["labels"] = g[v]
 _label = "label" if v_label == "names" else v_label
trace_patch["labels"] = trace_data[attr_value]
 _label = "label" if attr_label == "names" else attr_label
 mapping_labels[_label] = "%{label}"
 else:
result[k] = g[v]
trace_patch[attr_name] = trace_data[attr_value]
 else:
 if v:
result[k] = g[v]
 mapping_labels[v_label] = "%%{%s}" % k
 if attr_value:
trace_patch[attr_name] = trace_data[attr_value]
 mapping_labels[attr_label] = "%%{%s}" % attr_name
 if trace_spec.constructor not in [
 go.Parcoords,
 go.Parcats,
 ]:
 hover_lines = [k + "=" + v for k, v in mapping_labels.items()]
result["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return result, fit_results
trace_patch["hovertemplate"] = hover_header + "<br>".join(hover_lines)
 return trace_patch, fit_results


def configure_axes(args, constructor, fig, orders):
Expand DownExpand Up@@ -1015,8 +1027,8 @@ def _check_dataframe_all_leaves(df):
 null_indices = np.nonzero(null_mask.any(axis=1).values)[0]
 for null_row_index in null_indices:
 row = null_mask.iloc[null_row_index]
indices = np.nonzero(row.values)[0]
 if not row[indices[0] :].all():
i = np.nonzero(row.values)[0][0]
 if not row[i:].all():
 raise ValueError(
 "None entries cannot have not-None children",
 df_sorted.iloc[null_row_index],
Expand DownExpand Up@@ -1058,6 +1070,7 @@ def process_dataframe_hierarchy(args):
 path = [new_col_name if x == col_name else x for x in path]
 df[new_col_name] = series_to_copy
 # ------------ Define aggregation functions --------------------------------

 def aggfunc_discrete(x):
 uniques = x.unique()
 if len(uniques) == 1:
Expand Down