英文:
a weird gap on the y-axis
问题
在你提供的绘图中，垂直的蓝色波浪线代表y轴的起始点，并不是一个实际的数据点。这是由于在你的数据中，y轴的刻度从-0.1开始，而数据的最小值（fit.0.025quant中的最小值）比-0.1要小，因此出现了这个间隙。
要修复这个问题，你可以考虑将y轴的刻度从更接近数据范围的数值开始，例如从-0.05或-0.02开始，以确保y轴的起点与数据的最小值对齐，不会出现间隙。
这是一个修改后的绘图代码示例：
plot <- ggplot(df, aes(x = polity2, y = mean)) +
geom_pointrange(aes(ymin = fit.0.025quant, ymax = fit.0.975quant), color = "red") +
scale_y_continuous(breaks = seq(-0.02, 1.2, 0.05)) +
scale_x_continuous(breaks = seq(0, 1, 0.05))
通过调整y轴刻度的起点，你可以让y轴与数据对齐，消除间隙。
英文:
My data is:
structure(list(country = c("Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria", "Austria",
"Austria", "Austria", "Austria", "Austria", "Austria"), year = c(1800,
1801, 1802, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811,
1812, 1813, 1814, 1815, 1816, 1817, 1818, 1819, 1820, 1821, 1822,
1823, 1824, 1825, 1826, 1827, 1828, 1829, 1830, 1831, 1832, 1833,
1834, 1835, 1836, 1837, 1838, 1839, 1840, 1841, 1842, 1843, 1844,
1845, 1846, 1847, 1848, 1849, 1850, 1851, 1852, 1853, 1854, 1855,
1856, 1857, 1858, 1859, 1860, 1861, 1862, 1863, 1864, 1865, 1866,
1867, 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877,
1878, 1879, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888,
1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898),
polity2 = c(0, 0, 0, 0, 0, NA, 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, 0.2, 0.2, 0.2,
0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.3, 0.3,
0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3,
0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3,
0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3
), fit.0.025quant = c(-0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.360467515197976, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, -0.0228377190990235, -0.0228377190990235,
-0.0228377190990235, 0.16674339213966, 0.16674339213966,
0.16674339213966, 0.16674339213966, 0.16674339213966, 0.16674339213966,
0.16674339213966, 0.16674339213966, 0.16674339213966, 0.16674339213966,
0.16674339213966, 0.16674339213966, 0.16674339213966, 0.242005668666783,
0.242005668666783, 0.242005668666783, 0.242005668666783,
0.242005668666783, 0.242005668666783, 0.242005668666783,
0.242005668666783, 0.242005668666783, 0.242005668666783,
0.242005668666783, 0.242005668666783, 0.242005668666783,
0.242005668666783, 0.242005668666783, 0.242005668666783,
0.242005668666783, 0.242005668666783, 0.242005668666783,
0.242005668666783, 0.242005668666783, 0.242005668666783,
0.242005668666783, 0.242005668666783, 0.242005668666783,
0.242005668666783, 0.242005668666783, 0.242005668666783,
0.242005668666783, 0.242005668666783, 0.242005668666783,
0.242005668666783, 0.242005668666783, 0.242005668666783,
0.242005668666783, 0.242005668666783, 0.242005668666783,
0.242005668666783), fit.mean = c(3.14825130391602e-08, 2.60205063225599e-08,
2.59559368612124e-08, 2.5984794678656e-08, 2.83391441725141e-08,
2.52942314305284e-09, 2.83391440436086e-08, 2.59847906547622e-08,
2.5955396223965e-08, 2.59551516402278e-08, 2.5955149733964e-08,
2.5955149659684e-08, 2.59551496875235e-08, 2.59551496990232e-08,
2.59551496697443e-08, 2.59551496762558e-08, 2.59551497113832e-08,
2.59551496830708e-08, 2.59551496000976e-08, 2.59551496100631e-08,
2.59551498151052e-08, 2.59551496273394e-08, 2.59551496256576e-08,
2.59551496498655e-08, 2.59551496827474e-08, 2.59551496919159e-08,
2.59551497380275e-08, 2.59551498119649e-08, 2.5955149656671e-08,
2.5955149726764e-08, 2.59551496311154e-08, 2.59551496629923e-08,
2.59551496748244e-08, 2.59551496503481e-08, 2.59551496599462e-08,
2.59551498719153e-08, 2.59551516171938e-08, 2.59551725579831e-08,
2.59554430639403e-08, 2.59589965355424e-08, 2.60069290863896e-08,
2.6671828589446e-08, 3.61804464990433e-08, 1.76724037684815e-07,
2.32931085826976e-06, 3.65813076312562e-05, 0.000604208916987207,
0.0104234834558744, 0.189576586574593, 0.199395843381036,
0.199963470607777, 0.199997722599642, 0.199999875188186,
0.200000015755743, 0.200000025596808, 0.200000031016018,
0.200000101335746, 0.200001177632703, 0.200018303630534,
0.200302117262285, 0.205211743139791, 0.294788313124213,
0.299697934741236, 0.299981748281017, 0.299998874277316,
0.299999950570704, 0.3000000208425, 0.300000025596811, 0.300000025929259,
0.300000025953225, 0.300000025955003, 0.30000002595514, 0.300000025955146,
0.300000025955149, 0.30000002595515, 0.300000025955149, 0.300000025955149,
0.300000025955151, 0.300000025955148, 0.30000002595515, 0.300000025955149,
0.300000025955151, 0.300000025955148, 0.300000025955146,
0.300000025955149, 0.300000025955151, 0.30000002595515, 0.300000025955151,
0.30000002595515, 0.300000025955152, 0.300000025955152, 0.300000025955148,
0.300000025955146, 0.300000025955149, 0.300000025955148,
0.300000025955149, 0.300000025955148, 0.300000025955149,
0.300000025955146), fit.0.975quant = c(0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.895588490397268, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.0398209805304305,
0.0398209805304305, 0.0398209805304305, 0.230715038583087,
0.230715038583087, 0.230715038583087, 0.230715038583087,
0.230715038583087, 0.230715038583087, 0.230715038583087,
0.230715038583087, 0.230715038583087, 0.230715038583087,
0.230715038583087, 0.230715038583087, 0.230715038583087,
0.3453320450646, 0.3453320450646, 0.3453320450646, 0.3453320450646,
0.3453320450646, 0.3453320450646, 0.3453320450646, 0.3453320450646,
0.3453320450646, 0.3453320450646, 0.3453320450646, 0.3453320450646,
0.3453320450646, 0.3453320450646, 0.3453320450646, 0.3453320450646,
0.3453320450646, 0.3453320450646, 0.3453320450646, 0.3453320450646,
0.3453320450646, 0.3453320450646, 0.3453320450646, 0.3453320450646,
0.3453320450646, 0.3453320450646, 0.3453320450646, 0.3453320450646,
0.3453320450646, 0.3453320450646, 0.3453320450646, 0.3453320450646,
0.3453320450646, 0.3453320450646, 0.3453320450646, 0.3453320450646,
0.3453320450646, 0.3453320450646), mean = c(0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.179349478235255, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.000219534613172309,
0.000219534613172309, 0.000219534613172309, 0.200204245756936,
0.200204245756936, 0.200204245756936, 0.200204245756936,
0.200204245756936, 0.200204245756936, 0.200204245756936,
0.200204245756936, 0.200204245756936, 0.200204245756936,
0.200204245756936, 0.200204245756936, 0.200204245756936,
0.299996880329696, 0.299996880329696, 0.299996880329696,
0.299996880329696, 0.299996880329696, 0.299996880329696,
0.299996880329696, 0.299996880329696, 0.299996880329696,
0.299996880329696, 0.299996880329696, 0.299996880329696,
0.299996880329696, 0.299996880329696, 0.299996880329696,
0.299996880329696, 0.299996880329696, 0.299996880329696,
0.299996880329696, 0.299996880329696, 0.299996880329696,
0.299996880329696, 0.299996880329696, 0.299996880329696,
0.299996880329696, 0.299996880329696, 0.299996880329696,
0.299996880329696, 0.299996880329696, 0.299996880329696,
0.299996880329696, 0.299996880329696, 0.299996880329696,
0.299996880329696, 0.299996880329696, 0.299996880329696,
0.299996880329696, 0.299996880329696)), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -99L), groups = structure(list(
polity2 = c(0, 0.2, 0.3, NA), .rows = structure(list(c(1L,
2L, 3L, 4L, 5L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L,
16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L,
28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L, 39L,
40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L), 49:61, 62:99,
6L), ptype = integer(0), class = c("vctrs_list_of", "vctrs_vctr",
"list"))), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA,
-4L), .drop = TRUE))
>
And I want to produce plot as:
plot <- ggplot(df,
aes(x = polity2, y = mean)) + geom_pointrange(aes(ymin = fit.0.025quant, ymax = fit.0.975quant),
color = "red") + scale_y_continuous(breaks=seq(-0.1,1.2,0.05)) + scale_x_continuous(breaks=seq(0,1,0.05))
Which produces plot as:
Why is there a weird gap on the y-axis (marked with a wave blue line)? And how it can be removed?
It is supposed to show y-axis and x-axis to be coming from the same origin, as any typical graph.
Could you guys please help me out with this?
答案1
得分: 2
The issue is that the range of fit.0.025quant extends to -.36... which is reflected in the limits of the y scale. However, this happens for only one obs for which the polity2 value is missing and hence it will not be taken into account for the geom_pointrange. One option to fix that would be to drop the observation(s) with a missing value for polity2:
问题在于fit.0.025quant的范围延伸到了-.36...，这反映在y轴的scale的限制中。然而，这仅发生在一个观测中，其中polity2的值缺失，因此不会被考虑在geom_pointrange中。修复的一个选项是删除具有缺失值的polity2的观测：
library(ggplot2)
library(dplyr)
df %>%
filter(!is.na(polity2)) %>%
ggplot(
aes(x = polity2, y = mean)
) +
geom_pointrange(aes(ymin = fit.0.025quant, ymax = fit.0.975quant),
color = "red"
) +
scale_y_continuous(breaks = seq(-0.1, 1.2, 0.05)) +
scale_x_continuous(breaks = seq(0, 1, 0.05))
<details>
<summary>英文:</summary>
The issue is that the range of `fit.0.025quant` extends to `-.36...` which is reflected in the `limits` of the y `scale`. However, this happens for only one obs for which the `polity2` value is missing and hence it will not be taken into account for the `geom_pointrange`. One option to fix that would be to drop the observation(s) with a missing value for `polity2`:
library(ggplot2)
library(dplyr)
df |>
filter(!is.na(polity2)) |>
ggplot(
aes(x = polity2, y = mean)
) +
geom_pointrange(aes(ymin = fit.0.025quant, ymax = fit.0.975quant),
color = "red"
) +
scale_y_continuous(breaks = seq(-0.1, 1.2, 0.05)) +
scale_x_continuous(breaks = seq(0, 1, 0.05))
[![enter image description here][1]][1]
[1]: https://i.stack.imgur.com/DFlEG.png
</details>
# 答案2
**得分**: 1
我们需要将 `limits` 添加到 `breaks` 中：
```R
ggplot(df, aes(x = polity2, y = mean)) +
geom_pointrange(aes(ymin = fit.0.025quant, ymax = fit.0.975quant), color = "red") +
scale_x_continuous(limits = c(-0.1, 0.5), breaks = seq(-0.1, 0.5, by = 0.05)) +
scale_y_continuous(limits = c(-0.1, 1.2), breaks = seq(-0.1, 1.2, by = 0.05))
英文:
We have to add limits to breaks:
ggplot(df, aes(x = polity2, y = mean)) +
geom_pointrange(aes(ymin = fit.0.025quant, ymax = fit.0.975quant), color = "red") +
scale_x_continuous(limits = c(-0.1, 0.5), breaks = seq(-0.1, 0.5, by = 0.05)) +
scale_y_continuous(limits = c(-0.1, 1.2), breaks = seq(-0.1, 1.2, by = 0.05))
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