Can Dplyr pipe a data frame into the table(function)?

I have a data frame of the following type:

Date        X1 ....
2010-01-01  4
2010-01-02  5
2010-01-27  4
2012-03-10  2
...

So I am using the table() function to see the frequency of sampling each day/month. That means that I'm not looking at the values of each sampling, only it there is one that day. The thing is, I have generated an additional column called "season" using the "hydroTSM" package. So my idea is to use the following code:

df %>%
  filter(date >= "2010-01-01") %>%
  filter(date <= "2010-12-30") %>%
  table(.$season)

But it gives me error.

Error in xtrm.data.frame(x) :cannot xtfrm data frames.

However if I save it as a "date" variable and then do "table(date$season)" I get what I wanted.

 data <-  df %>%
      filter(date >= "2010-01-01") %>%
      filter(date <= "2010-12-30") %>%
      as.data.frame(df$date, df$season)

table(data$season)

Is it possible to do this with pipes?

While I would also use the exposition pipe, another option would be to use with.

library(magrittr)
mtcars %>% 
  with(table(cyl, gear))

The thing to understand is that %>% places the left hand side into the corresponding position of the right hand side (typically in the first slot).

Thus, mtcars %>% table(.$cyl) translates to table(mtcars, .$cyl) as you can easily verify:

trace(table, quote(print(list(...))))

# Tracing table(., .$cyl) on entry 
# [[1]]
#                      mpg cyl  disp  hp drat    wt  qsec vs am gear carb
# Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
# Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
# Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
# Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
# Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
# Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
# Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
# Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
# Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
# Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
# Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
# Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
# Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
# Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
# Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
# Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
# Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
# Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
# Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
# Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
# Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
# Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
# AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
# Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
# Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
# Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
# Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
# Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
# Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
# Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
# Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
# Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2
# 
# [[2]]
#  [1] 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4
# 
# Error in xtfrm.data.frame(x) : 
#   (converted from warning) cannot xtfrm data frames

That is, technically the term .$cyl is understood and properly evaluated, but tidyverse does not recognize it as it does with the single dot (i.e. use the LHS at this position and not in the first:

f <- function(a, b) print(list(a = a, b = b))

2 %>% f("a")
# $a
# [1] 2

# $b
# [1] "a"

# 2 %>% f("a", .)
# $a
# [1] "a"

# $b
# [1] 2

In the second case, tidyverse recognize the presence of . and thus does not add it again as the first argument.

Update

The IMHO cleanest approach is to surround the RHS with curly braces like this, which overrides the default behavior of placing the dot in the first slot:

mtcars %>% 
  { table(.$cyl, .$gear) }

You can use the exposition pipe %$% to use the columns as argument without a data argument.

library(magrittr)
mtcars %$% 
  table(cyl, gear)

#    gear
# cyl  3  4  5
#   4  1  8  2
#   6  2  4  1
#   8 12  0  2

When dot is nested, lhs is still placed first. This can be avoided with {}.
See What are the differences and use cases of the five Magrittr Pipes %>%, %<>%, %$%, %!>% and %T>%? for additional alternatives.

library(magrittr)
mtcars %>% 
  {table(.$cyl)}
#
# 4  6  8 
#11  7 14