`to_json` does not handle color as `np.nan` properly
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- Lenguaje dominante
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Descripción
When creating a scatter plot with colors including np.nan the figure shows fine.
import json
import numpy as np
import plotly.graph_objects as go
go.Figure(go.Scatter(x=[0, 0], y=[0, 1], marker={"color": [0, np.nan]}))
However, if I convert the figure to JSON and load it back, there will be an error.
fig = go.Figure(go.Scatter(x=[0, 0], y=[0, 1], marker={"color": [0, np.nan]}))
go.Figure(**json.loads(fig.to_json()))
Error message:
ValueError:
Invalid element(s) received for the 'color' property of scatter.marker
Invalid elements include: [None]
The 'color' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
- An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
- A named CSS color:
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, rebeccapurple, saddlebrown, salmon,
sandybrown, seagreen, seashell, sienna, silver,
skyblue, slateblue, slategray, slategrey, snow,
springgreen, steelblue, tan, teal, thistle, tomato,
turquoise, violet, wheat, white, whitesmoke,
yellow, yellowgreen
- A number that will be interpreted as a color
according to scatter.marker.colorscale
- A list or array of any of the above
Interestingly, the to_plotly_json method works fine:
fig = go.Figure(go.Scatter(x=[0, 0], y=[0, 1], marker={"color": [0, np.nan]}))
go.Figure(**json.loads(json.dumps(fig.to_plotly_json())))
Questions: Is this the expected behavior for the to_json method, and why it behaves differently from the to_plotly_json method?
Guía de contribución
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
Línea de trabajo
Reproduce el problema usando Figure.to_json, Figure.to_plotly_json y el ejemplo del color del marcador de scatter incluido en el informe. Compara estos puntos de entrada de serialización para determinar cómo se representa np.nan durante el round-trip y, a continuación, añade una prueba de regresión que cubra el comportamiento coherente previsto.
Escrito por el modelo de indexación a partir del texto del issue.
Evaluación
- Stack tecnológico
- numpy, python
- Área
- data-visualization
- Tipo de issue
- Error
- Dificultad
- 3/5
- Tiempo estimado
- 1-2 días
- Estado de actividad
- Estancado
- Claridad
- Bastante claro
- Aptitud para principiantes
- 45/100