Selection a specific date

[Radamas]

Good morning,
I'm working with a cvs file, where among the different columns I have "Year". For my analysis, I need to select only the year 2015. Is there a way to do it?

[nirgrahamuk]

import the csv to R, then filter it.

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[Radamas]

Thanks for your reply. I was wondering, the code here is: filter(flights, month == 1, day == 1). In my case, I should use the name of my data set, but then I cannot find a way to select just the year 2015. I have no month or days, I just have Country, Year, GDP and so on. If I read further, I see that to filter by year I could use: ```
filter(FB, date >= as.Date("2013-01-01"), date <= as.Date("2013-12-31"))
The problem, again, is date I don't have months or days to insert

[cactusoxbird]

In the same way that you used month == 1 or day == 1, you can filter for year == 2015. If this column is just an integer then you don't need to worry about creating a date value to filter with. For example:

library(tidyverse)
library(gapminder)

head(gapminder)
#> # A tibble: 6 x 6
#>   country     continent  year lifeExp      pop gdpPercap
#>   <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
#> 1 Afghanistan Asia       1952    28.8  8425333      779.
#> 2 Afghanistan Asia       1957    30.3  9240934      821.
#> 3 Afghanistan Asia       1962    32.0 10267083      853.
#> 4 Afghanistan Asia       1967    34.0 11537966      836.
#> 5 Afghanistan Asia       1972    36.1 13079460      740.
#> 6 Afghanistan Asia       1977    38.4 14880372      786.

filter(gapminder, year == 1952)
#> # A tibble: 142 x 6
#>    country     continent  year lifeExp      pop gdpPercap
#>    <fct>       <fct>     <int>   <dbl>    <int>     <dbl>
#>  1 Afghanistan Asia       1952    28.8  8425333      779.
#>  2 Albania     Europe     1952    55.2  1282697     1601.
#>  3 Algeria     Africa     1952    43.1  9279525     2449.
#>  4 Angola      Africa     1952    30.0  4232095     3521.
#>  5 Argentina   Americas   1952    62.5 17876956     5911.
#>  6 Australia   Oceania    1952    69.1  8691212    10040.
#>  7 Austria     Europe     1952    66.8  6927772     6137.
#>  8 Bahrain     Asia       1952    50.9   120447     9867.
#>  9 Bangladesh  Asia       1952    37.5 46886859      684.
#> 10 Belgium     Europe     1952    68    8730405     8343.
#> # ... with 132 more rows

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