在dygraph上绘制多个系列

问题描述 投票：0回答：1

我正在尝试在 dygraph 折线图上绘制多个系列。 df 的结构如下：

structure(list(Date = structure(c(4216, 4216, 4217, 4217, 4218, 
4218, 4219, 4219, 4220, 4220, 4221, 4221, 4222, 4222, 4223, 4223, 
4224, 4224, 4225, 4225, 4226, 4226, 4227, 4227, 4228, 4228, 4229, 
4229, 4230, 4230, 4231, 4231, 4232, 4232, 4233, 4233, 4234, 4234, 
4235, 4235, 4236, 4236, 4237, 4237, 4238, 4238, 4239, 4239, 4240, 
4240, 4241, 4241, 4242, 4242, 4243, 4243, 4244, 4244, 4245, 4245, 
4246, 4246, 4247, 4247, 4248, 4248, 4249, 4249, 4250, 4250, 4251, 
4251, 4252, 4252, 4253, 4253, 4254, 4254, 4255, 4255, 4256, 4256, 
4257, 4257, 4258, 4258, 4259, 4259, 4260, 4260, 4261, 4261, 4262, 
4262, 4263, 4263, 4264, 4264, 4265, 4265, 4266, 4266, 4267, 4267, 
4268, 4268, 4269, 4269, 4270, 4270, 4271, 4271, 4272, 4272, 4273, 
4273, 4274, 4274, 4275, 4275, 4276, 4276, 4277, 4277, 4278, 4278, 
4279, 4279, 4280, 4280, 4281, 4281, 4282, 4282, 4283, 4283, 4284, 
4284, 4285, 4285, 4286, 4286, 4287, 4287, 4288, 4288, 4289, 4289, 
4290, 4290, 4291, 4291, 4292, 4292, 4293, 4293, 4294, 4294, 4295, 
4295, 4296, 4296, 4297, 4297, 4298, 4298, 4299, 4299, 4300, 4300, 
4301, 4301, 4302, 4302, 4303, 4303, 4304, 4304, 4305, 4305, 4306, 
4306, 4307, 4307, 4308, 4308, 4309, 4309, 4310, 4310, 4311, 4311, 
4312, 4312, 4313, 4313, 4314, 4314, 4315, 4315, 4316, 4316, 4317, 
4317, 4318, 4318, 4319, 4319, 4320, 4320, 4321, 4321, 4322, 4322, 
4323, 4323, 4324, 4324, 4325, 4325, 4326, 4326, 4327, 4327, 4328, 
4328, 4329, 4329, 4330, 4330, 4331, 4331, 4332, 4332, 4333, 4333, 
4334, 4334, 4335, 4335, 4336, 4336, 4337, 4337, 4338, 4338, 4339, 
4339, 4340, 4340, 4341, 4341, 4342, 4342, 4343, 4343, 4344, 4344, 
4345, 4345, 4346, 4346, 4347, 4347, 4348, 4348, 4349, 4349, 4350, 
4350, 4351, 4351, 4352, 4352, 4353, 4353, 4354, 4354, 4355, 4355, 
4356, 4356, 4357, 4357, 4358, 4358, 4359, 4359, 4360, 4360, 4361, 
4361, 4362, 4362, 4363, 4363, 4364, 4364, 4365, 4365, 4366, 4366, 
4367, 4367, 4368, 4368, 4369, 4369, 4370, 4370, 4371, 4371, 4372, 
4372, 4373, 4373, 4374, 4374, 4375, 4375, 4376, 4376, 4377, 4377, 
4378, 4378, 4379, 4379, 4380, 4380, 4381, 4381, 4382, 4382, 4383, 
4383, 4384, 4384, 4385, 4385, 4386, 4386, 4387, 4387, 4388, 4388, 
4389, 4389, 4390, 4390, 4391, 4391, 4392, 4392, 4393, 4393, 4394, 
4394, 4395, 4395, 4396, 4396, 4397, 4397, 4398, 4398), class = "Date"), 
    Em_balde = c("Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short", "Medium", "Short", "Medium", "Short", "Medium", 
    "Short"), Valor = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 
    0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 
    1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 
    0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 
    1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 
    0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 
    1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 
    0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 
    1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 
    0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 
    1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 
    0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 
    1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 
    0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 
    1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 
    0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 
    1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 
    0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 1000, 0, 
    1000, 0, 1000, 0)), class = c("grouped_df", "tbl_df", "tbl", 
"data.frame"), row.names = c(NA, -366L), groups = structure(list(
    Date = structure(c(4216, 4217, 4218, 4219, 4220, 4221, 4222, 
    4223, 4224, 4225, 4226, 4227, 4228, 4229, 4230, 4231, 4232, 
    4233, 4234, 4235, 4236, 4237, 4238, 4239, 4240, 4241, 4242, 
    4243, 4244, 4245, 4246, 4247, 4248, 4249, 4250, 4251, 4252, 
    4253, 4254, 4255, 4256, 4257, 4258, 4259, 4260, 4261, 4262, 
    4263, 4264, 4265, 4266, 4267, 4268, 4269, 4270, 4271, 4272, 
    4273, 4274, 4275, 4276, 4277, 4278, 4279, 4280, 4281, 4282, 
    4283, 4284, 4285, 4286, 4287, 4288, 4289, 4290, 4291, 4292, 
    4293, 4294, 4295, 4296, 4297, 4298, 4299, 4300, 4301, 4302, 
    4303, 4304, 4305, 4306, 4307, 4308, 4309, 4310, 4311, 4312, 
    4313, 4314, 4315, 4316, 4317, 4318, 4319, 4320, 4321, 4322, 
    4323, 4324, 4325, 4326, 4327, 4328, 4329, 4330, 4331, 4332, 
    4333, 4334, 4335, 4336, 4337, 4338, 4339, 4340, 4341, 4342, 
    4343, 4344, 4345, 4346, 4347, 4348, 4349, 4350, 4351, 4352, 
    4353, 4354, 4355, 4356, 4357, 4358, 4359, 4360, 4361, 4362, 
    4363, 4364, 4365, 4366, 4367, 4368, 4369, 4370, 4371, 4372, 
    4373, 4374, 4375, 4376, 4377, 4378, 4379, 4380, 4381, 4382, 
    4383, 4384, 4385, 4386, 4387, 4388, 4389, 4390, 4391, 4392, 
    4393, 4394, 4395, 4396, 4397, 4398), class = "Date"), .rows = structure(list(
        1:2, 3:4, 5:6, 7:8, 9:10, 11:12, 13:14, 15:16, 17:18, 
        19:20, 21:22, 23:24, 25:26, 27:28, 29:30, 31:32, 33:34, 
        35:36, 37:38, 39:40, 41:42, 43:44, 45:46, 47:48, 49:50, 
        51:52, 53:54, 55:56, 57:58, 59:60, 61:62, 63:64, 65:66, 
        67:68, 69:70, 71:72, 73:74, 75:76, 77:78, 79:80, 81:82, 
        83:84, 85:86, 87:88, 89:90, 91:92, 93:94, 95:96, 97:98, 
        99:100, 101:102, 103:104, 105:106, 107:108, 109:110, 
        111:112, 113:114, 115:116, 117:118, 119:120, 121:122, 
        123:124, 125:126, 127:128, 129:130, 131:132, 133:134, 
        135:136, 137:138, 139:140, 141:142, 143:144, 145:146, 
        147:148, 149:150, 151:152, 153:154, 155:156, 157:158, 
        159:160, 161:162, 163:164, 165:166, 167:168, 169:170, 
        171:172, 173:174, 175:176, 177:178, 179:180, 181:182, 
        183:184, 185:186, 187:188, 189:190, 191:192, 193:194, 
        195:196, 197:198, 199:200, 201:202, 203:204, 205:206, 
        207:208, 209:210, 211:212, 213:214, 215:216, 217:218, 
        219:220, 221:222, 223:224, 225:226, 227:228, 229:230, 
        231:232, 233:234, 235:236, 237:238, 239:240, 241:242, 
        243:244, 245:246, 247:248, 249:250, 251:252, 253:254, 
        255:256, 257:258, 259:260, 261:262, 263:264, 265:266, 
        267:268, 269:270, 271:272, 273:274, 275:276, 277:278, 
        279:280, 281:282, 283:284, 285:286, 287:288, 289:290, 
        291:292, 293:294, 295:296, 297:298, 299:300, 301:302, 
        303:304, 305:306, 307:308, 309:310, 311:312, 313:314, 
        315:316, 317:318, 319:320, 321:322, 323:324, 325:326, 
        327:328, 329:330, 331:332, 333:334, 335:336, 337:338, 
        339:340, 341:342, 343:344, 345:346, 347:348, 349:350, 
        351:352, 353:354, 355:356, 357:358, 359:360, 361:362, 
        363:364, 365:366), ptype = integer(0), class = c("vctrs_list_of", 
    "vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -183L), .drop = TRUE))

我通常能够通过执行 xts(x = df$valor, order.by = df$Date) 将其转换为可用的 dygraphs 格式。

但是因为有多个“Em_balde”，导致了一个问题。我想做的是为“Em_balde”中包含的每个系列都有一个单独的行。

对于我一直在使用的单个数据系列：

dygraph(df, main = "Em Balde - Médio") %>%
  dySeries("V1", label = "Valor") %>%
  dyOptions(labelsUTC = TRUE, fillGraph=TRUE, fillAlpha=0.1, drawGrid = FALSE, stepPlot = TRUE) %>%
  dyHighlight(highlightCircleSize = 5, highlightSeriesBackgroundAlpha = 0.2, hideOnMouseOut = FALSE)

但如上所述，这不适用于我的用例。

r xts dygraphs
1个回答
1
投票

要绘制多个系列，每条线都需要位于自己的列中。因此我必须使用pivot_wider来修改原始数据框，然后进行正常的xts转换来生成图表

最新问题
© www.soinside.com 2019 - 2024. All rights reserved.