Question

我一直在仔细阅读DOT航空公司的数据，并试图创建每个航空公司的乘客从特定机场到所有其他车站的年度（YOY）变化的堆积条形图。

我还想按从指定机场到每个车站的总人数（market.ppd）订购x轴（例如，这套原产地机场是PHL，其最高目的地是MCO接下来是迈阿密，LAS等。）

当YOY数据单独为正或负时，x轴保持有序，但一旦我尝试将条形图与两者叠加，则默认返回字母顺序。有些电台只会出现正YOY变化或YOY变化为负，而this帖中的示例对每个类别都有正负值。

我的预感是，一旦发现某些电台没有相应的正/负值，ggplot会将电平恢复为字母顺序。一旦我将负值附加到每个电台的正值，有没有办法保留有序电平？

Plot with both positive and negative values

library(ggplot2)

OD <- data.frame(
      destination = c('MCO', 'MCO', 'MCO', 'MCO', 'MCO', 'MCO', 'MCO', 'Miami', 'Miami', 'Miami', 'Miami', 'Miami', 'Miami', 'LAS', 'LAS', 'LAS', 'LAS', 'Chicago', 'Chicago', 'Chicago', 'Chicago', 'Chicago', 'Chicago', 'Los Angeles', 'Los Angeles', 'Bay Area', 'Bay Area', 'Bay Area', 'Bay Area', 'Bay Area', 'BOS', 'BOS', 'BOS', 'ATL', 'ATL', 'ATL', 'ATL', 'ATL', 'ATL', 'TPA', 'TPA', 'TPA', 'TPA', 'Dallas', 'Dallas', 'Dallas', 'DEN', 'DEN', 'DEN', 'PHX', 'PHX', 'PHX', 'PHX', 'PHX', 'CUN', 'CUN', 'RSW', 'RSW', 'RSW', 'SAN', 'SAN', 'SJU', 'Houston', 'Houston', 'MSY', 'MSP', 'MSP', 'CLT', 'CLT', 'CLT', 'MBJ', 'MBJ', 'PUJ', 'PUJ', 'PUJ'),
      carrier = c('US', 'F9', 'WN', 'AA', 'FL', 'UA', 'DL', 'F9', 'US', 'DL', 'WN', 'UA', 'FL', 'AA', 'US', 'UA', 'NK', 'US', 'NK', 'F9', 'WN', 'UA', 'AA', 'WN', 'VX', 'US', 'DL', 'AA', 'VX', 'UA', 'US', 'B6', 'AA', 'US', 'WN', 'F9', 'DL', 'AA', 'FL', 'US', 'F9', 'WN', 'UA', 'DL', 'WN', 'US', 'US', 'WN', 'DL', 'US', 'WN', 'AA', 'DL', 'UA', 'US', 'F9', 'US', 'WN', 'UA', 'US', 'AA', 'AA', 'DL', 'WN', 'DL', 'F9', 'DL', 'F9', 'US', 'UA', 'AA', 'US', 'AA', 'F9', 'US'),
      market.ppd = c(1242, 1242, 1242, 1242, 1242, 1242, 1242, 1056, 1056, 1056, 1056, 1056, 1056, 645, 645, 645, 645, 641, 641, 641, 641, 641, 641, 526, 526, 498, 498, 498, 498, 498, 492, 492, 492, 482, 482, 482, 482, 482, 482, 478, 478, 478, 478, 399, 399, 399, 333, 333, 333, 298, 298, 298, 298, 298, 243, 243, 232, 232, 232, 213, 213, 205, 198, 198, 173, 163, 163, 160, 160, 160, 152, 152, 147, 147, 147),
      YOY = c(110, 96, 26, 15, -39, -23, -18, 52, 47, 11, -48, -22, -10, 8, -49, -11, -6, 15, 10, 8, 8, -12, -9, 9, -56, 35, 8, 6, -32, -12, 9, 7, 6, 47, 43, 16, 8, 7, -34, 44, 39, 8, -9, 13, 7, -28, 21, 7, 6, 37, 7, 6, -10, -7, 16, 9, 60, -37, -6, 19, -9, 6, 9, -6, -6, 16, -7, 20, 11, -6, 9, -24, 8, -11, -7),
      label.placement = c(55, 158, 219, 239, -20, -50, -71, 26, 75, 105, -24, -59, -75, 4, -25, -55, -63, 8, 20, 30, 38, -6, -17, 4, -28, 17, 39, 46, -16, -38, 4, 12, 19, 23, 68, 98, 110, 118, -17, 22, 64, 87, -5, 6, 17, -14, 10, 24, 31, 18, 40, 47, -5, -14, 8, 20, 30, -19, -40, 9, -5, 3, 4, -3, -3, 8, -4, 10, 26, -3, 5, -12, 4, -6, -15))

OD$destination <- factor(OD$destination, OD$destination)

ggplot() +
geom_bar(data = OD[OD$YOY > 0, ], aes(x = destination, y = YOY, fill = carrier), stat = 'identity') + 
geom_text(data = OD[OD$YOY > 0, ], aes(x = destination, y = label.placement, label = carrier), size = 2) + 
geom_bar(data = OD[OD$YOY < 0, ], aes(x = destination, y = YOY, fill = carrier), stat = 'identity') + 
geom_text(data = OD[OD$YOY < 0, ], aes(x = destination, y = label.placement, label = carrier), size = 2) +
theme(axis.text.x = element_text(size = 10, vjust = .5, angle = 90), legend.position = 'none')

Answer 1

您可以定义订单，然后告诉ggplot相应地显示数据：

library(ggplot2)

OD <- data.frame(
  destination = c('MCO', 'MCO', 'MCO', 'MCO', 'MCO', 'MCO', 'MCO', 'Miami', 'Miami', 'Miami', 'Miami', 'Miami', 'Miami', 'LAS', 'LAS', 'LAS', 'LAS', 'Chicago', 'Chicago', 'Chicago', 'Chicago', 'Chicago', 'Chicago', 'Los Angeles', 'Los Angeles', 'Bay Area', 'Bay Area', 'Bay Area', 'Bay Area', 'Bay Area', 'BOS', 'BOS', 'BOS', 'ATL', 'ATL', 'ATL', 'ATL', 'ATL', 'ATL', 'TPA', 'TPA', 'TPA', 'TPA', 'Dallas', 'Dallas', 'Dallas', 'DEN', 'DEN', 'DEN', 'PHX', 'PHX', 'PHX', 'PHX', 'PHX', 'CUN', 'CUN', 'RSW', 'RSW', 'RSW', 'SAN', 'SAN', 'SJU', 'Houston', 'Houston', 'MSY', 'MSP', 'MSP', 'CLT', 'CLT', 'CLT', 'MBJ', 'MBJ', 'PUJ', 'PUJ', 'PUJ'),
  carrier = c('US', 'F9', 'WN', 'AA', 'FL', 'UA', 'DL', 'F9', 'US', 'DL', 'WN', 'UA', 'FL', 'AA', 'US', 'UA', 'NK', 'US', 'NK', 'F9', 'WN', 'UA', 'AA', 'WN', 'VX', 'US', 'DL', 'AA', 'VX', 'UA', 'US', 'B6', 'AA', 'US', 'WN', 'F9', 'DL', 'AA', 'FL', 'US', 'F9', 'WN', 'UA', 'DL', 'WN', 'US', 'US', 'WN', 'DL', 'US', 'WN', 'AA', 'DL', 'UA', 'US', 'F9', 'US', 'WN', 'UA', 'US', 'AA', 'AA', 'DL', 'WN', 'DL', 'F9', 'DL', 'F9', 'US', 'UA', 'AA', 'US', 'AA', 'F9', 'US'),
  market.ppd = c(1242, 1242, 1242, 1242, 1242, 1242, 1242, 1056, 1056, 1056, 1056, 1056, 1056, 645, 645, 645, 645, 641, 641, 641, 641, 641, 641, 526, 526, 498, 498, 498, 498, 498, 492, 492, 492, 482, 482, 482, 482, 482, 482, 478, 478, 478, 478, 399, 399, 399, 333, 333, 333, 298, 298, 298, 298, 298, 243, 243, 232, 232, 232, 213, 213, 205, 198, 198, 173, 163, 163, 160, 160, 160, 152, 152, 147, 147, 147),
  YOY = c(110, 96, 26, 15, -39, -23, -18, 52, 47, 11, -48, -22, -10, 8, -49, -11, -6, 15, 10, 8, 8, -12, -9, 9, -56, 35, 8, 6, -32, -12, 9, 7, 6, 47, 43, 16, 8, 7, -34, 44, 39, 8, -9, 13, 7, -28, 21, 7, 6, 37, 7, 6, -10, -7, 16, 9, 60, -37, -6, 19, -9, 6, 9, -6, -6, 16, -7, 20, 11, -6, 9, -24, 8, -11, -7),
  label.placement = c(55, 158, 219, 239, -20, -50, -71, 26, 75, 105, -24, -59, -75, 4, -25, -55, -63, 8, 20, 30, 38, -6, -17, 4, -28, 17, 39, 46, -16, -38, 4, 12, 19, 23, 68, 98, 110, 118, -17, 22, 64, 87, -5, 6, 17, -14, 10, 24, 31, 18, 40, 47, -5, -14, 8, 20, 30, -19, -40, 9, -5, 3, 4, -3, -3, 8, -4, 10, 26, -3, 5, -12, 4, -6, -15))

OD$destination <- factor(OD$destination, OD$destination)
neworder <- unique(levels(OD$destination))

ggplot() +
  geom_bar(data = OD[OD$YOY > 0, ], aes(x = destination, y = YOY, fill = carrier), stat = 'identity') + 
  geom_text(data = OD[OD$YOY > 0, ], aes(x = destination, y = label.placement, label = carrier), size = 2) + 
  geom_bar(data = OD[OD$YOY < 0, ], aes(x = destination, y = YOY, fill = carrier), stat = 'identity') + 
  geom_text(data = OD[OD$YOY < 0, ], aes(x = destination, y = label.placement, label = carrier), size = 2) +
  theme(axis.text.x = element_text(size = 10, vjust = .5, angle = 90), legend.position = 'none')+
  scale_x_discrete(limits=c(neworder))

ggplot具有负值的堆积条形图

1 个答案: