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Salman Yousaf

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

The R programming language is used to perform statistical analysis. We can use built-in functions to accomplish our tasks. The ** mean()** method is used to compute the arithmetic mean of the argument vector

`x`

. We can use the `mean()`

method either column-wise or row-wise, depending on the logic of the program.The

meanis calculated by dividing the sum of all values by the total number of values in the dataset.

The syntax of the `mean()`

function to calculate the average of values of `x`

is as follows:

```
mean(x, trim = 0, na.rm = FALSE,...)
```

`x`

: A vector of numeric, logical, date, or date-time values. For complex vectors,`trim`

should be zero.`trim`

: Used to drop values from both sides of vector`x`

before computing the mean. The default value is 0.`na.rm`

: A boolean field that can be set to`TRUE`

to remove`NA`

(Not Available) values before computing the mean. The default value is`False`

.

`mean()`

returns a numeric or complex vector with length one or `NA_real_`

.

In the code snippet below, we calculate the mean of vector `x`

in line 5. In line 6, we return the return type.

# Create a vector.x <- c(6,14,6,14.2,18,2,63,-21,9,-5,-4)# Evaluate mean of numbersmean_value <- mean(x,trim = 0)typeof(mean_value)# Printing resultscat("Mean is:", mean_value)

The demo code below also calculates the mean of the vector `x`

. `trim = 0.2`

, which means it will drop two values (6,14) from the left and two values (-5,-4) from the right. Then `mean()`

method will evaluate the arithmetic mean of the remaining values, `(6,14.2,18,2,63,-21,9)`

.

# Create a vector.x <- c(6,14,6,14.2,18,2,63,-21,9,-5,-4)# Find Mean with trim = 0.2mean_value <- mean(x,trim = 0.2)cat("Trimed Mean: ", mean_value)

In line 2, we have a vector of numeric values containing an `NA`

value. The `mean()`

method in line 4 will return `NA`

. So, in line 7, we set `na.rm= TRUE`

, which removes `NA`

values, and compute the mean of the remaining values.

# Create a vector.x <- c(6,14,6,14.2,18,NA,2,63,-21,9,-5,-4)# Find mean.mean_value <- mean(x)cat("Wrong Output before: ", mean_value)# Find mean dropping NA values.mean_value <- mean(x,na.rm = TRUE)cat("\nAfter removing : ", mean_value)

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Salman Yousaf

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

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