为 ggmap 上的每个点添加图例而不是组变量
Add legend for every point on ggmap instead of a group variable
我得到了以下数据框：
df1 <- structure(list(City = c("Ahmadnagar", "Ahmedabad", "Akola", "Amaravati",
"Aurangabad", "Belgaum", "Bellary", "Bengaluru", "Bhavnagar",
"Bhiwandi", "Bhuj", "Bhusaval", "Bidar", "Bijapur", "Chanda",
"Chikka Mandya", "Chirala", "Davangere", "Ghandinagar", "Gulbarga",
"Guntur", "Hindupur", "Hospet", "Hubli", "Kagaznagar", "Kakinada",
"Kalyan", "Khanapur", "Kolar", "Kolhapur", "Kurnool", "Latur",
"Machilipatnam", "Malegaon Camp", "Mangalore", "Mumbai", "Mysore",
"Nanded", "Nandyal", "Nasik", "Navsari", "Nellore", "Ongole",
"Parbhani", "Porbandar", "Proddatur", "Pune", "Raichur", "Rajahmundry",
"Rajkot", "Sangli", "Shimoga", "Surat", "Tirupati", "Vadodara",
"Vishakhapatnam", "Vizianagaram"), State = c("Maharashtra", "Gujarat",
"Maharashtra", "Maharashtra", "Maharashtra", "Karnataka", "Karnataka",
"Karnataka", "Gujarat", "Maharashtra", "Gujarat", "Maharashtra",
"Karnataka", "Karnataka", "Maharashtra", "Karnataka", "Andhra Pradesh",
"Karnataka", "Gujarat", "Karnataka", "Andhra Pradesh", "Andhra Pradesh",
"Karnataka", "Karnataka", "Andhra Pradesh", "Andhra Pradesh",
"Maharashtra", "Maharashtra", "Karnataka", "Maharashtra", "Andhra Pradesh",
"Maharashtra", "Andhra Pradesh", "Maharashtra", "Karnataka",
"Maharashtra", "Karnataka", "Maharashtra", "Andhra Pradesh",
"Maharashtra", "Gujarat", "Andhra Pradesh", "Andhra Pradesh",
"Maharashtra", "Gujarat", "Andhra Pradesh", "Maharashtra", "Karnataka",
"Andhra Pradesh", "Gujarat", "Maharashtra", "Karnataka", "Gujarat",
"Andhra Pradesh", "Gujarat", "Andhra Pradesh", "Andhra Pradesh"
), Lat = c(19.094571, 23.025793, 20.709569, 20.933272, 19.880943,
15.862643, 15.142049, 12.977063, 21.774455, 19.300229, 23.253972,
21.043649, 17.913309, 16.827715, 19.950758, 12.545602, 15.823849,
14.469237, 23.216667, 17.335827, 16.299737, 13.828065, 15.269537,
15.349955, 19.331589, 16.960361, 19.243703, 21.273716, 13.137679,
16.695633, 15.828865, 18.399487, 16.187466, 20.569974, 12.865371,
18.987807, 12.292664, 19.160227, 15.477994, 19.999963, 20.85,
14.449918, 15.503565, 19.268553, 21.641346, 14.7502, 18.513271,
16.205459, 17.005171, 22.291606, 16.856777, 13.932424, 21.195944,
13.635505, 22.299405, 17.704052, 18.11329), Long = c(74.738432,
72.587265, 76.998103, 77.75152, 75.346739, 74.508534, 76.92398,
77.587106, 72.152496, 73.058813, 69.669281, 75.785058, 77.530105,
75.718988, 79.295229, 76.895078, 80.352187, 75.92375, 72.683333,
76.83757, 80.457293, 77.491425, 76.387103, 75.138619, 79.466051,
82.238086, 73.135537, 76.117376, 78.129989, 74.231669, 78.036021,
76.584252, 81.13888, 74.515415, 74.842432, 72.836447, 76.638543,
77.314971, 78.483605, 73.776887, 72.916667, 79.986967, 80.044541,
76.770807, 69.600868, 78.548129, 73.849852, 77.35567, 81.777839,
70.793217, 74.569196, 75.572555, 72.830232, 79.419888, 73.208119,
83.297663, 83.397743)), class = c("grouped_df", "tbl_df", "tbl",
"data.frame"), row.names = c(NA, -57L), groups = structure(list(
State = c("Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh",
"Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh",
"Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh",
"Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh",
"Gujarat", "Gujarat", "Gujarat", "Gujarat", "Gujarat", "Gujarat",
"Gujarat", "Gujarat", "Gujarat", "Karnataka", "Karnataka",
"Karnataka", "Karnataka", "Karnataka", "Karnataka", "Karnataka",
"Karnataka", "Karnataka", "Karnataka", "Karnataka", "Karnataka",
"Karnataka", "Karnataka", "Karnataka", "Maharashtra", "Maharashtra",
"Maharashtra", "Maharashtra", "Maharashtra", "Maharashtra",
"Maharashtra", "Maharashtra", "Maharashtra", "Maharashtra",
"Maharashtra", "Maharashtra", "Maharashtra", "Maharashtra",
"Maharashtra", "Maharashtra", "Maharashtra", "Maharashtra"
), City = c("Chirala", "Guntur", "Hindupur", "Kagaznagar",
"Kakinada", "Kurnool", "Machilipatnam", "Nandyal", "Nellore",
"Ongole", "Proddatur", "Rajahmundry", "Tirupati", "Vishakhapatnam",
"Vizianagaram", "Ahmedabad", "Bhavnagar", "Bhuj", "Ghandinagar",
"Navsari", "Porbandar", "Rajkot", "Surat", "Vadodara", "Belgaum",
"Bellary", "Bengaluru", "Bidar", "Bijapur", "Chikka Mandya",
"Davangere", "Gulbarga", "Hospet", "Hubli", "Kolar", "Mangalore",
"Mysore", "Raichur", "Shimoga", "Ahmadnagar", "Akola", "Amaravati",
"Aurangabad", "Bhiwandi", "Bhusaval", "Chanda", "Kalyan",
"Khanapur", "Kolhapur", "Latur", "Malegaon Camp", "Mumbai",
"Nanded", "Nasik", "Parbhani", "Pune", "Sangli"), .rows = structure(list(
17L, 21L, 22L, 25L, 26L, 31L, 33L, 39L, 42L, 43L, 46L,
49L, 54L, 56L, 57L, 2L, 9L, 11L, 19L, 41L, 45L, 50L,
53L, 55L, 6L, 7L, 8L, 13L, 14L, 16L, 18L, 20L, 23L, 24L,
29L, 35L, 37L, 48L, 52L, 1L, 3L, 4L, 5L, 10L, 12L, 15L,
27L, 28L, 30L, 32L, 34L, 36L, 38L, 40L, 44L, 47L, 51L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -57L), .drop = TRUE))
我正在从中生成这样的图：
这是我使用的代码：
india_centroid <- c(68.18625, 6, 97.41529, 37)
req_zoom <- calc_zoom(Long, Lat, data = df1)
map_type = get_map(location = india_centroid, zoom = req_zoom, maptype = "roadmap")
p <- ggmap(map_type, extent = "panel", legend = "bottomright", size = c(500, 600))
p + geom_point(aes(x = Long, y = Lat, color = State), data = df1) +
ggtitle("Cities in India")
因此，如您所见，这些点是基于 State 列的颜色。图例显示了他们所属州的名称。但是，我需要图例来显示每个 City 的名称而不是状态，而颜色与每个状态相同。
我知道这没有意义，因为同一州的城市会重复颜色。但我需要知道这是否可能。如果可能的话，如何实现。
一个选项是创建一个命名的颜色向量，它为每个 City 分配 State 颜色。这样做，您可以将 City 映射到颜色 aes 上，并通过 scale_color_manual:
根据颜色向量设置颜色
library(ggmap)
library(dplyr)
# State colors
col_state <- data.frame(
State = sort(unique(df1$State)),
color = scales::hue_pal()(length(unique(df1$State)))
)
# City colors
col_city <- df1 %>%
ungroup() %>%
select(City, State) %>%
distinct() %>%
left_join(col_state) %>%
select(-State) %>%
tibble::deframe()
india_centroid <- c(68.18625, 6, 97.41529, 37)
req_zoom <- calc_zoom(Long, Lat, data = df1)
map_type = get_map(location = india_centroid, zoom = req_zoom, maptype = "roadmap")
p <- ggmap(map_type, extent = "panel", legend = "bottomright", size = c(500, 600))
p + geom_point(aes(x = Long, y = Lat, color = City), data = df1) +
scale_color_manual(values = col_city) +
ggtitle("Cities in India")
编辑 要按州订购图例，您必须相应地设置中断。为此，我建议按州重新排列您的数据集，并使用 forcats::fct_inorder 将您的城市列转换为一个因素。之后可以根据City系数的levels设置色阶的breaks：
df1 <- df1 %>%
arrange(State, City) %>%
mutate(City = forcats::fct_inorder(City))
p + geom_point(aes(x = Long, y = Lat, color = City), data = df1) +
scale_color_manual(values = col_city, breaks = levels(df1$City)) +
ggtitle("Cities in India")
我得到了以下数据框：
df1 <- structure(list(City = c("Ahmadnagar", "Ahmedabad", "Akola", "Amaravati",
"Aurangabad", "Belgaum", "Bellary", "Bengaluru", "Bhavnagar",
"Bhiwandi", "Bhuj", "Bhusaval", "Bidar", "Bijapur", "Chanda",
"Chikka Mandya", "Chirala", "Davangere", "Ghandinagar", "Gulbarga",
"Guntur", "Hindupur", "Hospet", "Hubli", "Kagaznagar", "Kakinada",
"Kalyan", "Khanapur", "Kolar", "Kolhapur", "Kurnool", "Latur",
"Machilipatnam", "Malegaon Camp", "Mangalore", "Mumbai", "Mysore",
"Nanded", "Nandyal", "Nasik", "Navsari", "Nellore", "Ongole",
"Parbhani", "Porbandar", "Proddatur", "Pune", "Raichur", "Rajahmundry",
"Rajkot", "Sangli", "Shimoga", "Surat", "Tirupati", "Vadodara",
"Vishakhapatnam", "Vizianagaram"), State = c("Maharashtra", "Gujarat",
"Maharashtra", "Maharashtra", "Maharashtra", "Karnataka", "Karnataka",
"Karnataka", "Gujarat", "Maharashtra", "Gujarat", "Maharashtra",
"Karnataka", "Karnataka", "Maharashtra", "Karnataka", "Andhra Pradesh",
"Karnataka", "Gujarat", "Karnataka", "Andhra Pradesh", "Andhra Pradesh",
"Karnataka", "Karnataka", "Andhra Pradesh", "Andhra Pradesh",
"Maharashtra", "Maharashtra", "Karnataka", "Maharashtra", "Andhra Pradesh",
"Maharashtra", "Andhra Pradesh", "Maharashtra", "Karnataka",
"Maharashtra", "Karnataka", "Maharashtra", "Andhra Pradesh",
"Maharashtra", "Gujarat", "Andhra Pradesh", "Andhra Pradesh",
"Maharashtra", "Gujarat", "Andhra Pradesh", "Maharashtra", "Karnataka",
"Andhra Pradesh", "Gujarat", "Maharashtra", "Karnataka", "Gujarat",
"Andhra Pradesh", "Gujarat", "Andhra Pradesh", "Andhra Pradesh"
), Lat = c(19.094571, 23.025793, 20.709569, 20.933272, 19.880943,
15.862643, 15.142049, 12.977063, 21.774455, 19.300229, 23.253972,
21.043649, 17.913309, 16.827715, 19.950758, 12.545602, 15.823849,
14.469237, 23.216667, 17.335827, 16.299737, 13.828065, 15.269537,
15.349955, 19.331589, 16.960361, 19.243703, 21.273716, 13.137679,
16.695633, 15.828865, 18.399487, 16.187466, 20.569974, 12.865371,
18.987807, 12.292664, 19.160227, 15.477994, 19.999963, 20.85,
14.449918, 15.503565, 19.268553, 21.641346, 14.7502, 18.513271,
16.205459, 17.005171, 22.291606, 16.856777, 13.932424, 21.195944,
13.635505, 22.299405, 17.704052, 18.11329), Long = c(74.738432,
72.587265, 76.998103, 77.75152, 75.346739, 74.508534, 76.92398,
77.587106, 72.152496, 73.058813, 69.669281, 75.785058, 77.530105,
75.718988, 79.295229, 76.895078, 80.352187, 75.92375, 72.683333,
76.83757, 80.457293, 77.491425, 76.387103, 75.138619, 79.466051,
82.238086, 73.135537, 76.117376, 78.129989, 74.231669, 78.036021,
76.584252, 81.13888, 74.515415, 74.842432, 72.836447, 76.638543,
77.314971, 78.483605, 73.776887, 72.916667, 79.986967, 80.044541,
76.770807, 69.600868, 78.548129, 73.849852, 77.35567, 81.777839,
70.793217, 74.569196, 75.572555, 72.830232, 79.419888, 73.208119,
83.297663, 83.397743)), class = c("grouped_df", "tbl_df", "tbl",
"data.frame"), row.names = c(NA, -57L), groups = structure(list(
State = c("Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh",
"Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh",
"Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh",
"Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh", "Andhra Pradesh",
"Gujarat", "Gujarat", "Gujarat", "Gujarat", "Gujarat", "Gujarat",
"Gujarat", "Gujarat", "Gujarat", "Karnataka", "Karnataka",
"Karnataka", "Karnataka", "Karnataka", "Karnataka", "Karnataka",
"Karnataka", "Karnataka", "Karnataka", "Karnataka", "Karnataka",
"Karnataka", "Karnataka", "Karnataka", "Maharashtra", "Maharashtra",
"Maharashtra", "Maharashtra", "Maharashtra", "Maharashtra",
"Maharashtra", "Maharashtra", "Maharashtra", "Maharashtra",
"Maharashtra", "Maharashtra", "Maharashtra", "Maharashtra",
"Maharashtra", "Maharashtra", "Maharashtra", "Maharashtra"
), City = c("Chirala", "Guntur", "Hindupur", "Kagaznagar",
"Kakinada", "Kurnool", "Machilipatnam", "Nandyal", "Nellore",
"Ongole", "Proddatur", "Rajahmundry", "Tirupati", "Vishakhapatnam",
"Vizianagaram", "Ahmedabad", "Bhavnagar", "Bhuj", "Ghandinagar",
"Navsari", "Porbandar", "Rajkot", "Surat", "Vadodara", "Belgaum",
"Bellary", "Bengaluru", "Bidar", "Bijapur", "Chikka Mandya",
"Davangere", "Gulbarga", "Hospet", "Hubli", "Kolar", "Mangalore",
"Mysore", "Raichur", "Shimoga", "Ahmadnagar", "Akola", "Amaravati",
"Aurangabad", "Bhiwandi", "Bhusaval", "Chanda", "Kalyan",
"Khanapur", "Kolhapur", "Latur", "Malegaon Camp", "Mumbai",
"Nanded", "Nasik", "Parbhani", "Pune", "Sangli"), .rows = structure(list(
17L, 21L, 22L, 25L, 26L, 31L, 33L, 39L, 42L, 43L, 46L,
49L, 54L, 56L, 57L, 2L, 9L, 11L, 19L, 41L, 45L, 50L,
53L, 55L, 6L, 7L, 8L, 13L, 14L, 16L, 18L, 20L, 23L, 24L,
29L, 35L, 37L, 48L, 52L, 1L, 3L, 4L, 5L, 10L, 12L, 15L,
27L, 28L, 30L, 32L, 34L, 36L, 38L, 40L, 44L, 47L, 51L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), class = c("tbl_df", "tbl", "data.frame"
), row.names = c(NA, -57L), .drop = TRUE))
我正在从中生成这样的图：
这是我使用的代码：
india_centroid <- c(68.18625, 6, 97.41529, 37)
req_zoom <- calc_zoom(Long, Lat, data = df1)
map_type = get_map(location = india_centroid, zoom = req_zoom, maptype = "roadmap")
p <- ggmap(map_type, extent = "panel", legend = "bottomright", size = c(500, 600))
p + geom_point(aes(x = Long, y = Lat, color = State), data = df1) +
ggtitle("Cities in India")
因此，如您所见，这些点是基于 State 列的颜色。图例显示了他们所属州的名称。但是，我需要图例来显示每个 City 的名称而不是状态，而颜色与每个状态相同。
我知道这没有意义，因为同一州的城市会重复颜色。但我需要知道这是否可能。如果可能的话，如何实现。
一个选项是创建一个命名的颜色向量，它为每个 City 分配 State 颜色。这样做，您可以将 City 映射到颜色 aes 上，并通过 scale_color_manual:
library(ggmap)
library(dplyr)
# State colors
col_state <- data.frame(
State = sort(unique(df1$State)),
color = scales::hue_pal()(length(unique(df1$State)))
)
# City colors
col_city <- df1 %>%
ungroup() %>%
select(City, State) %>%
distinct() %>%
left_join(col_state) %>%
select(-State) %>%
tibble::deframe()
india_centroid <- c(68.18625, 6, 97.41529, 37)
req_zoom <- calc_zoom(Long, Lat, data = df1)
map_type = get_map(location = india_centroid, zoom = req_zoom, maptype = "roadmap")
p <- ggmap(map_type, extent = "panel", legend = "bottomright", size = c(500, 600))
p + geom_point(aes(x = Long, y = Lat, color = City), data = df1) +
scale_color_manual(values = col_city) +
ggtitle("Cities in India")
编辑 要按州订购图例，您必须相应地设置中断。为此，我建议按州重新排列您的数据集，并使用 forcats::fct_inorder 将您的城市列转换为一个因素。之后可以根据City系数的levels设置色阶的breaks：
df1 <- df1 %>%
arrange(State, City) %>%
mutate(City = forcats::fct_inorder(City))
p + geom_point(aes(x = Long, y = Lat, color = City), data = df1) +
scale_color_manual(values = col_city, breaks = levels(df1$City)) +
ggtitle("Cities in India")