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Format one-line chart descriptions to linewidth 75
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packages/python/plotly/plotly/express/_chart_types.py

Lines changed: 54 additions & 50 deletions
Original file line numberDiff line numberDiff line change
@@ -49,8 +49,8 @@ def scatter(
4949
height=None,
5050
):
5151
"""
52-
In a scatter plot, each row of `data_frame` is represented by a symbol mark
53-
in 2D space.
52+
In a scatter plot, each row of `data_frame` is represented by a symbol
53+
mark in 2D space.
5454
"""
5555
return make_figure(args=locals(), constructor=go.Scatter)
5656

@@ -93,9 +93,9 @@ def density_contour(
9393
height=None,
9494
):
9595
"""
96-
In a density contour plot, rows of `data_frame` are grouped together into
97-
contour marks to visualize the 2D distribution of an aggregate function
98-
`histfunc` (e.g. the count or sum) of the value `z`.
96+
In a density contour plot, rows of `data_frame` are grouped together
97+
into contour marks to visualize the 2D distribution of an aggregate
98+
function `histfunc` (e.g. the count or sum) of the value `z`.
9999
"""
100100
return make_figure(
101101
args=locals(),
@@ -150,8 +150,8 @@ def density_heatmap(
150150
):
151151
"""
152152
In a density heatmap, rows of `data_frame` are grouped together into
153-
colored rectangular tiles to visualize the 2D distribution of an aggregate
154-
function `histfunc` (e.g. the count or sum) of the value `z`.
153+
colored rectangular tiles to visualize the 2D distribution of an
154+
aggregate function `histfunc` (e.g. the count or sum) of the value `z`.
155155
"""
156156
return make_figure(
157157
args=locals(),
@@ -208,8 +208,8 @@ def line(
208208
height=None,
209209
):
210210
"""
211-
In a 2D line plot, each row of `data_frame` is represented as vertex of a
212-
polyline mark in 2D space.
211+
In a 2D line plot, each row of `data_frame` is represented as vertex of
212+
a polyline mark in 2D space.
213213
"""
214214
return make_figure(args=locals(), constructor=go.Scatter)
215215

@@ -249,9 +249,9 @@ def area(
249249
height=None,
250250
):
251251
"""
252-
In a stacked area plot, each row of `data_frame` is represented as vertex
253-
of a polyline mark in 2D space. The area between successive polylines is
254-
filled.
252+
In a stacked area plot, each row of `data_frame` is represented as
253+
vertex of a polyline mark in 2D space. The area between successive
254+
polylines is filled.
255255
"""
256256
return make_figure(
257257
args=locals(),
@@ -353,8 +353,8 @@ def histogram(
353353
):
354354
"""
355355
In a histogram, rows of `data_frame` are grouped together into a
356-
rectangular mark to visualize the 1D distribution of an aggregate function
357-
`histfunc` (e.g. the count or sum) of the value `y` (or `x` if
356+
rectangular mark to visualize the 1D distribution of an aggregate
357+
function `histfunc` (e.g. the count or sum) of the value `y` (or `x` if
358358
`orientation` is `'h'`).
359359
"""
360360
return make_figure(
@@ -407,8 +407,8 @@ def violin(
407407
height=None,
408408
):
409409
"""
410-
In a violin plot, rows of `data_frame` are grouped together into a curved
411-
mark to visualize their distribution.
410+
In a violin plot, rows of `data_frame` are grouped together into a
411+
curved mark to visualize their distribution.
412412
"""
413413
return make_figure(
414414
args=locals(),
@@ -462,11 +462,10 @@ def box(
462462
In a box plot, rows of `data_frame` are grouped together into a
463463
box-and-whisker mark to visualize their distribution.
464464
465-
Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The
466-
second quartile (Q2) is marked by a line inside the box. By
467-
default, the whiskers correspond to the box' edges +/- 1.5
468-
times the interquartile range (IQR: Q3-Q1), see "points" for
469-
other options.
465+
Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The second
466+
quartile (Q2) is marked by a line inside the box. By default, the
467+
whiskers correspond to the box' edges +/- 1.5 times the interquartile
468+
range (IQR: Q3-Q1), see "points" for other options.
470469
"""
471470
return make_figure(
472471
args=locals(),
@@ -510,8 +509,8 @@ def strip(
510509
height=None,
511510
):
512511
"""
513-
In a strip plot each row of `data_frame` is represented as a jittered mark
514-
within categories.
512+
In a strip plot each row of `data_frame` is represented as a jittered
513+
mark within categories.
515514
"""
516515
return make_figure(
517516
args=locals(),
@@ -576,8 +575,8 @@ def scatter_3d(
576575
height=None,
577576
):
578577
"""
579-
In a 3D scatter plot, each row of `data_frame` is represented by a symbol
580-
mark in 3D space.
578+
In a 3D scatter plot, each row of `data_frame` is represented by a
579+
symbol mark in 3D space.
581580
"""
582581
return make_figure(args=locals(), constructor=go.Scatter3d)
583582

@@ -623,8 +622,8 @@ def line_3d(
623622
height=None,
624623
):
625624
"""
626-
In a 3D line plot, each row of `data_frame` is represented as vertex of a
627-
polyline mark in 3D space.
625+
In a 3D line plot, each row of `data_frame` is represented as vertex of
626+
a polyline mark in 3D space.
628627
"""
629628
return make_figure(args=locals(), constructor=go.Scatter3d)
630629

@@ -699,8 +698,8 @@ def line_ternary(
699698
height=None,
700699
):
701700
"""
702-
In a ternary line plot, each row of `data_frame` is represented as vertex
703-
of a polyline mark in ternary coordinates.
701+
In a ternary line plot, each row of `data_frame` is represented as
702+
vertex of a polyline mark in ternary coordinates.
704703
"""
705704
return make_figure(args=locals(), constructor=go.Scatterternary)
706705

@@ -784,8 +783,8 @@ def line_polar(
784783
height=None,
785784
):
786785
"""
787-
In a polar line plot, each row of `data_frame` is represented as vertex of
788-
a polyline mark in polar coordinates.
786+
In a polar line plot, each row of `data_frame` is represented as vertex
787+
of a polyline mark in polar coordinates.
789788
"""
790789
return make_figure(args=locals(), constructor=go.Scatterpolar)
791790

@@ -860,8 +859,8 @@ def choropleth(
860859
height=None,
861860
):
862861
"""
863-
In a choropleth map, each row of `data_frame` is represented by a colored
864-
region mark on a map.
862+
In a choropleth map, each row of `data_frame` is represented by a
863+
colored region mark on a map.
865864
"""
866865
return make_figure(
867866
args=locals(),
@@ -905,8 +904,8 @@ def scatter_geo(
905904
height=None,
906905
):
907906
"""
908-
In a geographic scatter plot, each row of `data_frame` is represented by a
909-
symbol mark on a map.
907+
In a geographic scatter plot, each row of `data_frame` is represented
908+
by a symbol mark on a map.
910909
"""
911910
return make_figure(
912911
args=locals(),
@@ -1021,8 +1020,8 @@ def line_mapbox(
10211020
height=None,
10221021
):
10231022
"""
1024-
In a Mapbox line plot, each row of `data_frame` is represented as vertex of
1025-
a polyline mark on a Mapbox map.
1023+
In a Mapbox line plot, each row of `data_frame` is represented as
1024+
vertex of a polyline mark on a Mapbox map.
10261025
"""
10271026
return make_figure(args=locals(), constructor=go.Scattermapbox)
10281027

@@ -1057,8 +1056,9 @@ def scatter_matrix(
10571056
):
10581057
"""
10591058
In a scatter plot matrix (or SPLOM), each row of `data_frame` is
1060-
represented by a multiple symbol marks, one in each cell of a grid of 2D
1061-
scatter plots, which plot each pair of `dimensions` against each other.
1059+
represented by a multiple symbol marks, one in each cell of a grid of
1060+
2D scatter plots, which plot each pair of `dimensions` against each
1061+
other.
10621062
"""
10631063
return make_figure(
10641064
args=locals(), constructor=go.Splom, layout_patch=dict(dragmode="select")
@@ -1082,9 +1082,9 @@ def parallel_coordinates(
10821082
height=None,
10831083
):
10841084
"""
1085-
In a parallel coordinates plot, each row of `data_frame` is represented by
1086-
a polyline mark which traverses a set of parallel axes, one for each of the
1087-
`dimensions`.
1085+
In a parallel coordinates plot, each row of `data_frame` is represented
1086+
by a polyline mark which traverses a set of parallel axes, one for each
1087+
of the `dimensions`.
10881088
"""
10891089
return make_figure(args=locals(), constructor=go.Parcoords)
10901090

@@ -1106,10 +1106,10 @@ def parallel_categories(
11061106
height=None,
11071107
):
11081108
"""
1109-
In a parallel categories (or parallel sets) plot, each row of `data_frame`
1110-
is grouped with other rows that share the same values of `dimensions` and
1111-
then plotted as a polyline mark through a set of parallel axes, one for
1112-
each of the `dimensions`.
1109+
In a parallel categories (or parallel sets) plot, each row of
1110+
`data_frame` is grouped with other rows that share the same values of
1111+
`dimensions` and then plotted as a polyline mark through a set of
1112+
parallel axes, one for each of the `dimensions`.
11131113
"""
11141114
return make_figure(args=locals(), constructor=go.Parcats)
11151115

@@ -1136,7 +1136,8 @@ def pie(
11361136
hole=None,
11371137
):
11381138
"""
1139-
In a pie plot, each row of `data_frame` is represented as a sector of a pie.
1139+
In a pie plot, each row of `data_frame` is represented as a sector of a
1140+
pie.
11401141
"""
11411142
if color_discrete_sequence is not None:
11421143
layout_patch = {"piecolorway": color_discrete_sequence}
@@ -1228,7 +1229,8 @@ def treemap(
12281229
maxdepth=None,
12291230
):
12301231
"""
1231-
A treemap plot represents hierarchial data as nested rectangular sectors.
1232+
A treemap plot represents hierarchial data as nested rectangular
1233+
sectors.
12321234
"""
12331235
if color_discrete_sequence is not None:
12341236
layout_patch = {"treemapcolorway": color_discrete_sequence}
@@ -1275,7 +1277,8 @@ def funnel(
12751277
height=None,
12761278
):
12771279
"""
1278-
In a funnel plot, each row of `data_frame` is represented as a rectangular sector of a funnel.
1280+
In a funnel plot, each row of `data_frame` is represented as a
1281+
rectangular sector of a funnel.
12791282
"""
12801283
return make_figure(
12811284
args=locals(),
@@ -1305,7 +1308,8 @@ def funnel_area(
13051308
opacity=None,
13061309
):
13071310
"""
1308-
In a funnel area plot, each row of `data_frame` is represented as a trapezoidal sector of a funnel.
1311+
In a funnel area plot, each row of `data_frame` is represented as a
1312+
trapezoidal sector of a funnel.
13091313
"""
13101314
if color_discrete_sequence is not None:
13111315
layout_patch = {"funnelareacolorway": color_discrete_sequence}

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