在 R 中，如何从数据框中将数据拆分成组以在同一图形上绘制多条曲线？
In R, from a dataframe, how to split data into groups to plot multiple curves on the same graphic?
我有一个大数据框，如下所示：
> dput(sb_data_omit_1950[sample(nrow(sb_data_omit_1950), 50),])
structure(list(lat = c("56", "61", "57", "59", "58", "56", "58",
"65", "59", "65", "63", "65", "56", "59", "59", "57", "59", "60",
"56", "57", "60", "65", "64", "63", "63", "59", "59", "65", "59",
"58", "63", "59", "64", "59", "58", "59", "63", "56", "58", "59",
"57", "55", "58", "64", "62", "60", "57", "58", "60", "66"),
long = c(18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18,
18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18,
18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18,
18, 18, 18, 18, 18, 18, 18, 18), date = c("2009-02-07", "1995-03-04",
"2007-01-28", "2010-03-28", "2010-04-01", "2018-02-22", "2017-03-24",
"2014-04-16", "1983-03-20", "2016-04-02", "2020-04-14", "2020-04-02",
"2005-03-25", "2003-03-22", "2016-04-02", "2006-03-19", "2009-04-05",
"2009-01-22", "2016-03-05", "2013-02-23", "2017-03-17", "2020-03-25",
"2021-03-27", "2008-04-08", "2018-04-10", "1984-04-04", "2005-01-29",
"2019-04-03", "1983-04-10", "2006-03-26", "2010-03-29", "2006-03-18",
"2014-05-06", "2010-01-23", "2006-03-26", "2014-02-25", "2008-04-16",
"2021-02-16", "2011-03-30", "2013-03-07", "1975-03-22", "2015-02-01",
"2013-03-21", "2011-04-07", "2021-04-06", "2021-02-02", "2000-03-19",
"1983-02-26", "2010-04-03", "2017-03-28"), julian_day = c(38,
63, 28, 87, 91, 53, 83, 106, 79, 93, 105, 93, 84, 81, 93,
78, 95, 22, 65, 54, 76, 85, 86, 99, 100, 95, 29, 93, 100,
85, 88, 77, 126, 23, 85, 56, 107, 47, 89, 66, 81, 32, 80,
97, 96, 33, 79, 57, 93, 87), year = c(2009L, 1995L, 2007L,
2010L, 2010L, 2018L, 2017L, 2014L, 1983L, 2016L, 2020L, 2020L,
2005L, 2003L, 2016L, 2006L, 2009L, 2009L, 2016L, 2013L, 2017L,
2020L, 2021L, 2008L, 2018L, 1984L, 2005L, 2019L, 1983L, 2006L,
2010L, 2006L, 2014L, 2010L, 2006L, 2014L, 2008L, 2021L, 2011L,
2013L, 1975L, 2015L, 2013L, 2011L, 2021L, 2021L, 2000L, 1983L,
2010L, 2017L), decade = c("2000-2009", "1990-1999", "2000-2009",
"2010-2019", "2010-2019", "2010-2019", "2010-2019", "2010-2019",
"1980-1989", "2010-2019", "2020-2029", "2020-2029", "2000-2009",
"2000-2009", "2010-2019", "2000-2009", "2000-2009", "2000-2009",
"2010-2019", "2010-2019", "2010-2019", "2020-2029", "2020-2029",
"2000-2009", "2010-2019", "1980-1989", "2000-2009", "2010-2019",
"1980-1989", "2000-2009", "2010-2019", "2000-2009", "2010-2019",
"2010-2019", "2000-2009", "2010-2019", "2000-2009", "2020-2029",
"2010-2019", "2010-2019", "1970-1979", "2010-2019", "2010-2019",
"2010-2019", "2020-2029", "2020-2029", "2000-2009", "1980-1989",
"2010-2019", "2010-2019"), time = c(15L, 14L, 15L, 16L, 16L,
16L, 16L, 16L, 13L, 16L, 17L, 17L, 15L, 15L, 16L, 15L, 15L,
15L, 16L, 16L, 16L, 17L, 17L, 15L, 16L, 13L, 15L, 16L, 13L,
15L, 16L, 15L, 16L, 16L, 15L, 16L, 15L, 17L, 16L, 16L, 12L,
16L, 16L, 16L, 17L, 17L, 15L, 13L, 16L, 16L), lat_grouped = c("1",
"2", "1", "1", "1", "1", "1", "3", "1", "3", "2", "3", "1",
"1", "1", "1", "1", "2", "1", "1", "2", "3", "2", "2", "2",
"1", "1", "3", "1", "1", "2", "1", "2", "1", "1", "1", "2",
"1", "1", "1", "1", "1", "1", "2", "2", "2", "1", "1", "2",
"3")), row.names = c(21286L, 5843L, 16479L, 24246L, 24483L,
40513L, 39121L, 33554L, 2704L, 37376L, 48602L, 48008L, 12473L,
9593L, 37380L, 14123L, 22712L, 21155L, 36663L, 29846L, 38722L,
47518L, 51286L, 20119L, 42528L, 3132L, 11764L, 44966L, 2874L,
14406L, 24290L, 14081L, 33634L, 23125L, 14393L, 31981L, 20790L,
50057L, 26126L, 30068L, 1381L, 34000L, 30253L, 26612L, 51918L,
49677L, 7640L, 2677L, 24745L, 39308L), class = "data.frame")
> head(df)
lat long date julian_day year decade time lat_grouped
24 59 18 1951-03-22 81 1951 1950-1959 10 1
25 59 18 1951-04-08 98 1951 1950-1959 10 1
26 55 18 1952-02-03 34 1952 1950-1959 10 1
27 59 18 1952-03-08 68 1952 1950-1959 10 1
28 59 18 1953-02-22 53 1953 1950-1959 10 1
29 63 18 1953-03-12 71 1953 1950-1959 10 2
根据这些数据，我想计算给定十年（两个变量 decade 或 time 这是一个第一个的数值翻译）并将其与其他十年的数据绘制在同一图形上。
到目前为止，我已经成功地使用以下代码绘制了所有几十年的观察次数：
df %>%
ggplot(aes(x=julian_day)) +
geom_histogram(color="darkblue", fill="white", bins=152) +
xlim(0, 155) +
xlab("Day n°") + ylab("Count")
我的直觉是我应该使用 group_by(time) 但无法设法绘制某些选定的组。
输出应该看起来像绘制在同一张图上的多条高斯曲线。
有人能帮忙吗？非常感谢，如果缺少任何信息，我可以编辑我的 post :)
我不是 100% 确定你的最终输出应该是什么，但如果你想要一个图上的所有直方图：
df %>%
ggplot(aes(x=julian_day, fill = decade)) +
geom_histogram(bins=152) +
xlim(0, 155) +
xlab("Day n°") + ylab("Count")
如果在同一个图上分开直方图：
df %>%
ggplot(aes(x=julian_day, fill = decade)) +
geom_histogram(bins=152) +
xlim(0, 155) +
xlab("Day n°") + ylab("Count") +
facet_wrap(~decade, scales = "free")
如果只想select某几十年，可以加一个filter()参数。在这种情况下，最简单的方法是按年份过滤，因为它是数字：
# first and last decade
keeps <- c(min(df$year), max(df$year))
# or any decade by referencing a year within that decade
# keeps <- c(2009, 1985)
df %>% filter(year %in% keeps) %>%
ggplot(aes(x=julian_day, fill = decade)) +
geom_histogram(bins=152) +
xlim(0, 155) +
xlab("Day n°") + ylab("Count")
更新： 查看评论：
我们可以将 geom_histogram 应用计数统计与 geom_density 应用密度统计相结合：
df %>%
count(decade, julian_day) %>%
ggplot(aes(x = julian_day, fill=decade)) +
stat_bin(bins = 30, aes(y = ..count..)) +
geom_density(aes(y = ..density..*(nrow(df1)*0.8)), fill="yellow", color="#e9ecef", alpha=0.3)
是这样的吗？
library(tidyverse)
df %>%
count(decade, julian_day) %>%
ggplot(aes(x = julian_day, y=n, fill=decade))+
geom_col(position= position_dodge()) +
scale_y_continuous(breaks = function(x) unique(floor(pretty(seq(0, (max(x) + 1) * 1.1)))))
也许你想要这样的东西：
df %>%
count(decade, julian_day) %>%
ggplot(aes(x=julian_day, n)) +
geom_line(color="darkblue") +
xlim(0, 155) +
xlab("Day n°") +
ylab("Count") +
theme_bw()
输出：
我有一个大数据框，如下所示：
> dput(sb_data_omit_1950[sample(nrow(sb_data_omit_1950), 50),])
structure(list(lat = c("56", "61", "57", "59", "58", "56", "58",
"65", "59", "65", "63", "65", "56", "59", "59", "57", "59", "60",
"56", "57", "60", "65", "64", "63", "63", "59", "59", "65", "59",
"58", "63", "59", "64", "59", "58", "59", "63", "56", "58", "59",
"57", "55", "58", "64", "62", "60", "57", "58", "60", "66"),
long = c(18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18,
18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18,
18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18, 18,
18, 18, 18, 18, 18, 18, 18, 18), date = c("2009-02-07", "1995-03-04",
"2007-01-28", "2010-03-28", "2010-04-01", "2018-02-22", "2017-03-24",
"2014-04-16", "1983-03-20", "2016-04-02", "2020-04-14", "2020-04-02",
"2005-03-25", "2003-03-22", "2016-04-02", "2006-03-19", "2009-04-05",
"2009-01-22", "2016-03-05", "2013-02-23", "2017-03-17", "2020-03-25",
"2021-03-27", "2008-04-08", "2018-04-10", "1984-04-04", "2005-01-29",
"2019-04-03", "1983-04-10", "2006-03-26", "2010-03-29", "2006-03-18",
"2014-05-06", "2010-01-23", "2006-03-26", "2014-02-25", "2008-04-16",
"2021-02-16", "2011-03-30", "2013-03-07", "1975-03-22", "2015-02-01",
"2013-03-21", "2011-04-07", "2021-04-06", "2021-02-02", "2000-03-19",
"1983-02-26", "2010-04-03", "2017-03-28"), julian_day = c(38,
63, 28, 87, 91, 53, 83, 106, 79, 93, 105, 93, 84, 81, 93,
78, 95, 22, 65, 54, 76, 85, 86, 99, 100, 95, 29, 93, 100,
85, 88, 77, 126, 23, 85, 56, 107, 47, 89, 66, 81, 32, 80,
97, 96, 33, 79, 57, 93, 87), year = c(2009L, 1995L, 2007L,
2010L, 2010L, 2018L, 2017L, 2014L, 1983L, 2016L, 2020L, 2020L,
2005L, 2003L, 2016L, 2006L, 2009L, 2009L, 2016L, 2013L, 2017L,
2020L, 2021L, 2008L, 2018L, 1984L, 2005L, 2019L, 1983L, 2006L,
2010L, 2006L, 2014L, 2010L, 2006L, 2014L, 2008L, 2021L, 2011L,
2013L, 1975L, 2015L, 2013L, 2011L, 2021L, 2021L, 2000L, 1983L,
2010L, 2017L), decade = c("2000-2009", "1990-1999", "2000-2009",
"2010-2019", "2010-2019", "2010-2019", "2010-2019", "2010-2019",
"1980-1989", "2010-2019", "2020-2029", "2020-2029", "2000-2009",
"2000-2009", "2010-2019", "2000-2009", "2000-2009", "2000-2009",
"2010-2019", "2010-2019", "2010-2019", "2020-2029", "2020-2029",
"2000-2009", "2010-2019", "1980-1989", "2000-2009", "2010-2019",
"1980-1989", "2000-2009", "2010-2019", "2000-2009", "2010-2019",
"2010-2019", "2000-2009", "2010-2019", "2000-2009", "2020-2029",
"2010-2019", "2010-2019", "1970-1979", "2010-2019", "2010-2019",
"2010-2019", "2020-2029", "2020-2029", "2000-2009", "1980-1989",
"2010-2019", "2010-2019"), time = c(15L, 14L, 15L, 16L, 16L,
16L, 16L, 16L, 13L, 16L, 17L, 17L, 15L, 15L, 16L, 15L, 15L,
15L, 16L, 16L, 16L, 17L, 17L, 15L, 16L, 13L, 15L, 16L, 13L,
15L, 16L, 15L, 16L, 16L, 15L, 16L, 15L, 17L, 16L, 16L, 12L,
16L, 16L, 16L, 17L, 17L, 15L, 13L, 16L, 16L), lat_grouped = c("1",
"2", "1", "1", "1", "1", "1", "3", "1", "3", "2", "3", "1",
"1", "1", "1", "1", "2", "1", "1", "2", "3", "2", "2", "2",
"1", "1", "3", "1", "1", "2", "1", "2", "1", "1", "1", "2",
"1", "1", "1", "1", "1", "1", "2", "2", "2", "1", "1", "2",
"3")), row.names = c(21286L, 5843L, 16479L, 24246L, 24483L,
40513L, 39121L, 33554L, 2704L, 37376L, 48602L, 48008L, 12473L,
9593L, 37380L, 14123L, 22712L, 21155L, 36663L, 29846L, 38722L,
47518L, 51286L, 20119L, 42528L, 3132L, 11764L, 44966L, 2874L,
14406L, 24290L, 14081L, 33634L, 23125L, 14393L, 31981L, 20790L,
50057L, 26126L, 30068L, 1381L, 34000L, 30253L, 26612L, 51918L,
49677L, 7640L, 2677L, 24745L, 39308L), class = "data.frame")
> head(df)
lat long date julian_day year decade time lat_grouped
24 59 18 1951-03-22 81 1951 1950-1959 10 1
25 59 18 1951-04-08 98 1951 1950-1959 10 1
26 55 18 1952-02-03 34 1952 1950-1959 10 1
27 59 18 1952-03-08 68 1952 1950-1959 10 1
28 59 18 1953-02-22 53 1953 1950-1959 10 1
29 63 18 1953-03-12 71 1953 1950-1959 10 2
根据这些数据，我想计算给定十年（两个变量 decade 或 time 这是一个第一个的数值翻译）并将其与其他十年的数据绘制在同一图形上。
到目前为止，我已经成功地使用以下代码绘制了所有几十年的观察次数：
df %>%
ggplot(aes(x=julian_day)) +
geom_histogram(color="darkblue", fill="white", bins=152) +
xlim(0, 155) +
xlab("Day n°") + ylab("Count")
我的直觉是我应该使用 group_by(time) 但无法设法绘制某些选定的组。
输出应该看起来像绘制在同一张图上的多条高斯曲线。
有人能帮忙吗？非常感谢，如果缺少任何信息，我可以编辑我的 post :)
我不是 100% 确定你的最终输出应该是什么，但如果你想要一个图上的所有直方图：
df %>%
ggplot(aes(x=julian_day, fill = decade)) +
geom_histogram(bins=152) +
xlim(0, 155) +
xlab("Day n°") + ylab("Count")
如果在同一个图上分开直方图：
df %>%
ggplot(aes(x=julian_day, fill = decade)) +
geom_histogram(bins=152) +
xlim(0, 155) +
xlab("Day n°") + ylab("Count") +
facet_wrap(~decade, scales = "free")
如果只想select某几十年，可以加一个filter()参数。在这种情况下，最简单的方法是按年份过滤，因为它是数字：
# first and last decade
keeps <- c(min(df$year), max(df$year))
# or any decade by referencing a year within that decade
# keeps <- c(2009, 1985)
df %>% filter(year %in% keeps) %>%
ggplot(aes(x=julian_day, fill = decade)) +
geom_histogram(bins=152) +
xlim(0, 155) +
xlab("Day n°") + ylab("Count")
更新： 查看评论：
我们可以将 geom_histogram 应用计数统计与 geom_density 应用密度统计相结合：
df %>%
count(decade, julian_day) %>%
ggplot(aes(x = julian_day, fill=decade)) +
stat_bin(bins = 30, aes(y = ..count..)) +
geom_density(aes(y = ..density..*(nrow(df1)*0.8)), fill="yellow", color="#e9ecef", alpha=0.3)
library(tidyverse)
df %>%
count(decade, julian_day) %>%
ggplot(aes(x = julian_day, y=n, fill=decade))+
geom_col(position= position_dodge()) +
scale_y_continuous(breaks = function(x) unique(floor(pretty(seq(0, (max(x) + 1) * 1.1)))))
也许你想要这样的东西：
df %>%
count(decade, julian_day) %>%
ggplot(aes(x=julian_day, n)) +
geom_line(color="darkblue") +
xlim(0, 155) +
xlab("Day n°") +
ylab("Count") +
theme_bw()
输出：