install.packages("tidyverse")
library(tidyverse)
mmr <- readxl::read_excel("Maternal Mortality Ratio.xlsx", sheet = 1, col_names = TRUE, col_types = NULL)

ggplot() +
geom_histogram(data = subset(mmr, !is.na(2011.0)),
               aes(x = "2011.0"))

Error: StatBin requires a continuous x variable the x variable is discrete. Perhaps you want stat="count"?

> mmr
# A tibble: 999 × 215
`Maternal Mortality rate per 100 000` `1800.0` `1801.0` `1802.0` `1803.0` `1804.0` `1805.0` `1806.0` `1807.0`
                               <chr>    <dbl>    <dbl>    <dbl>    <dbl>    <dbl>    <dbl>    <dbl>    <dbl>
1                               Abkhazia       NA       NA       NA       NA       NA       NA       NA       NA
2                            Afghanistan       NA       NA       NA       NA       NA       NA       NA       NA
3                  Akrotiri and Dhekelia       NA       NA       NA       NA       NA       NA       NA       NA
4                                Albania       NA       NA       NA       NA       NA       NA       NA       NA
5                                Algeria       NA       NA       NA       NA       NA       NA       NA       NA
6                         American Samoa       NA       NA       NA       NA       NA       NA       NA       NA
7                                Andorra       NA       NA       NA       NA       NA       NA       NA       NA
8                                 Angola       NA       NA       NA       NA       NA       NA       NA       NA
9                               Anguilla       NA       NA       NA       NA       NA       NA       NA       NA
10                   Antigua and Barbuda       NA       NA       NA       NA       NA       NA       NA       NA
# ... with 989 more rows, and 206 more variables: `1808.0` <dbl>, `1809.0` <dbl>, `1810.0` <dbl>, `1811.0` <dbl>,
#   `1812.0` <dbl>, `1813.0` <dbl>, `1814.0` <dbl>, `1815.0` <dbl>, `1816.0` <dbl>, `1817.0` <dbl>, `1818.0` <dbl>,
#   `1819.0` <dbl>, `1820.0` <dbl>, `1821.0` <dbl>, `1822.0` <dbl>, `1823.0` <dbl>, `1824.0` <dbl>, `1825.0` <dbl>,
#   `1826.0` <dbl>, `1827.0` <dbl>, `1828.0` <dbl>, `1829.0` <dbl>, `1830.0` <dbl>, `1831.0` <dbl>, `1832.0` <dbl>,
#   `1833.0` <dbl>, `1834.0` <dbl>, `1835.0` <dbl>, `1836.0` <dbl>, `1837.0` <dbl>, `1838.0` <dbl>, `1839.0` <dbl>,
#   `1840.0` <dbl>, `1841.0` <dbl>, `1842.0` <dbl>, `1843.0` <dbl>, `1844.0` <dbl>, `1845.0` <dbl>, `1846.0` <dbl>,
#   `1847.0` <dbl>, `1848.0` <dbl>, `1849.0` <dbl>, `1850.0` <dbl>, `1851.0` <dbl>, `1852.0` <dbl>, `1853.0` <dbl>,
#   `1854.0` <dbl>, `1855.0` <dbl>, `1856.0` <dbl>, `1857.0` <dbl>, `1858.0` <dbl>, `1859.0` <dbl>, `1860.0` <dbl>,
#   `1861.0` <dbl>, `1862.0` <dbl>, `1863.0` <dbl>, `1864.0` <dbl>, `1865.0` <dbl>, `1866.0` <dbl>, `1867.0` <dbl>,
#   `1868.0` <dbl>, `1869.0` <dbl>, `1870.0` <dbl>, `1871.0` <dbl>, `1872.0` <dbl>, `1873.0` <dbl>, `1874.0` <dbl>,
#   `1875.0` <dbl>, `1876.0` <dbl>, `1877.0` <dbl>, `1878.0` <dbl>, `1879.0` <dbl>, `1880.0` <dbl>, `1881.0` <dbl>,
#   `1882.0` <dbl>, `1883.0` <dbl>, `1884.0` <dbl>, `1885.0` <dbl>, `1886.0` <dbl>, `1887.0` <dbl>, `1888.0` <dbl>,
#   `1889.0` <dbl>, `1890.0` <dbl>, `1891.0` <dbl>, `1892.0` <dbl>, `1893.0` <dbl>, `1894.0` <dbl>, `1895.0` <dbl>,
#   `1896.0` <dbl>, `1897.0` <dbl>, `1898.0` <dbl>, `1899.0` <dbl>, `1900.0` <dbl>, `1901.0` <dbl>, `1902.0` <dbl>,
#   `1903.0` <dbl>, `1904.0` <dbl>, `1905.0` <dbl>, `1906.0` <dbl>, `1907.0` <dbl>, ...

> str(mmr)
Classes ‘tbl_df’, ‘tbl’ and 'data.frame':   999 obs. of  215 variables:
 $ Maternal Mortality rate per 100 000: chr  "Abkhazia" "Afghanistan" "Akrotiri and Dhekelia" "Albania" ...
 $ 1800.0                             : num  NA NA NA NA NA NA NA NA NA NA ...
 $ 1801.0                             : num  NA NA NA NA NA NA NA NA NA NA ...

> typeof(mmr)
[1] "list"
> typeof(mmr$"2011.0")
[1] "double"
> is.double(mmr$"2011.0")
[1] TRUE
> is.numeric(mmr$"2011.0")
[1] TRUE
> is.character(mmr$"2011.0")
[1] FALSE
> is.character(mmr$"Maternal Mortality rate per 100 000")
[1] TRUE
> class(mmr$"2011.0")
[1] "numeric"
> class(mmr$"Maternal Mortality rate per 100 000")
[1] "character"

mmr[,'2011.0'] <- as.numeric(mmr[,'2011.0'])

mmr[,'2011.0'] <- as.numeric(as.character((mmr[,'2011.0']))

ggplot() +
geom_histogram(data = subset(mmr, !is.na(2011.0)),
             aes(x = "2011.0"))
Error: StatBin requires a continuous x variable the x variable is discrete. Perhaps you want stat="count"?

mmr <- readxl::read_excel("Maternal Mortality Ratio.xlsx", sheet = 1, col_names = TRUE, col_types = numeric)

Error in read_xlsx_(path, sheet, col_names = col_names, col_types = col_types,  : `col_types` must be a character vector or NULL