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I am following an example, the server.R

I plan to do a similar filter but am lost as to what %>% does.

 # Apply filters

    m <- all_movies %>%

      filter(

        Reviews >= reviews,

        Oscars >= oscars,

        Year >= minyear,

        Year <= maxyear,

        BoxOffice >= minboxoffice,

        BoxOffice <= maxboxoffice

      ) %>%

      arrange(Oscars)

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%>% is called the forward pipe operator in R. It provides a mechanism for chaining commands with a new forward-pipe operator, %>%. This operator will forward a value, or the result of an expression, into the next function call/expression.

It is defined by the package magrittr (CRAN) and is heavily used by dplyr (CRAN).

The role of this function is to pass the left-hand side of the operator to the first argument of the right-hand side of the operator.

For example:

 mtcars %>% head()

                   mpg cyl disp  hp drat    wt  qsec vs am gear carb

Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4

Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4

Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1

Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1

Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2

Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

Thus, mtcars %>% head() is equivalent to head(mtcars).

Often, %>% is called multiple times to "chain" functions together, which accomplishes the same result as nesting. For example in the chain below, mtcars passed to head(), then the result of that is passed to summary().

mtcars %>% head() %>% summary()

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The pipe operator ‘%>%’ in the R language is like a connector, which helps to connect two functions together. It takes the output value from one function and gives it as an input for the second function. You can understand it with a simple example:

numbers <- data.frame(value = c(1, 5, 3, 8, 2))

result <- numbers %>%

  filter(value > 2) %>%   

  arrange(value)          

print(result)

In the above example:

  • You can see that the result will be taking all the data from numbers

  • The filter is going to take all the output from the result and will select those values which are greater than 2

  • Then the arrange() function will take the output of the filter() function as an input for arrange.

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%>% in R is referred to as the pipe operator. It is mainly used within the dplyr and magrittr packages. The pipe operator lets you pass the output of one expression as the input to the next expression. In this way, it is more readable and concise, especially for data manipulation.

Key Features of %>%:

Chaining Commands: This allows you to chain multiple operations together in a linear fashion.

Improved Readability: Code is more readable and easier to understand since it follows a left-to-right flow.

Avoid Nesting: It minimizes the use of deeply nested function calls.

library(dplyr)

data <- data.frame(

  x = 1:5,

  z = c(2, 4, 3, 5, 1)

)

result <- data %>%

  filter(z > 2) %>

summarize(mean_x = mean(x))

 print(result)

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