rggplot2yaxis
a weird gap on the y-axis
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?
Solution
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))
- Conditional recursive formula in dplyr
- Current development in how to adjust individual x axis title using ggplot facet_wrap
- How to reorder a stacked bar chart in ggplot2?
- how can I render a quarto website to a single pdf
- Unable to install tidyverse package for r kernel in jupyter
- How to replace values in a matrix based on a conditional variable
- How can I make my enormous dataframe from wide to long in R?
- Summing polygons by value using terra in R
- R data.table updating a table based on an inner join with another table
- Regression using plm package and twoways effect, when data has NA
- R Shiny - How to have an action button that automatically downloads a csv file (Not download button?)
- Reference the current state of a piped object in R pipe subfunction
- geom_bar color according to 2 vars
- Use purrr::accumulate with condition
- Flip the text in facet rows in gglikert in R
- Count up and down from when condition is met, per category
- pretty_breaks does not working with geom_sf
- Display x-axis with ggh4x::facet_manual when blank panel area under graph
- Rearrage string elements by the number attached with it in rows
- horizontally match two ggplots in R
- Equivalent for R / dplyr's glimpse() function in Python for Panda dataframes?
- Why is reticulate::py_available() FALSE until I I run reticulate::py_run_string("")?
- Pass an optional argument to a custom function for use both directly and in an ellipsis construct
- Calculate relative change in time by group
- How to prevent text overflow in reactable.extras text field?
- Control new line placement of base::stop()
- Format for ordinal dates (day of month with suffixes -st, -nd, -rd, -th)
- How to produce a table.file for input in ReadMe: Software for Automated Content Analysis
- What is the purpose difference between README and vignette in R package?
- Create a multilines Readme.txt with R