Writing Functions

class: center, middle, inverse, title-slide

# <img src="figures/Thanksgiving-Day.jpg" /> Writing Functions - Loop
### <font size="5"> Son Nguyen </font>

---

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---
class: inverse, center, middle

# Loop

---
# Task

.pull-left[

|Name                                                | Age|Sex    |Survived |
|:---------------------------------------------------|---:|:------|:--------|
|Braund, Mr. Owen Harris                             |  22|male   |0        |
|Cumings, Mrs. John Bradley (Florence Briggs Thayer) |  38|female |1        |
|Heikkinen, Miss. Laina                              |  26|female |1        |
|Futrelle, Mrs. Jacques Heath (Lily May Peel)        |  35|female |1        |
|Allen, Mr. William Henry                            |  35|male   |0        |
- For each passenger, print out a sentence reporting the name and the age.

]

.pull-right[]

---
# Task

.pull-left[

]

.pull-right[

```r
for (i in 1:5)
{
  print(paste0(df$Name[i], ' is ', df$Age[i], ' year old.'))
}
```

]

---
# Task

.pull-left[

]

.pull-right[

```r
for (i in 1:5)
{
  print(paste0(df$Name[i], ' is ', df$Age[i], ' year old.'))
}
```

```
## [1] "Braund, Mr. Owen Harris is 22 year old."
## [1] "Cumings, Mrs. John Bradley (Florence Briggs Thayer) is 38 year old."
## [1] "Heikkinen, Miss. Laina is 26 year old."
## [1] "Futrelle, Mrs. Jacques Heath (Lily May Peel) is 35 year old."
## [1] "Allen, Mr. William Henry is 35 year old."
```

]

---
# Loop through a vector

.pull-left[

- Loop through a vector and print out all element of the vector.

]

.pull-right[

]

---
# Loop through a vector

.pull-left[

- Loop through a vector and print out all element of the vector.

]

.pull-right[

```r
x <- c('b','r','y','a','n','t')
for (i in x)
{
  print(i)
}
```

]

---
# Loop through a vector

.pull-left[

- Loop through a vector and print out all element of the vector.

]

.pull-right[

```r
x <- c('b','r','y','a','n','t')
for (i in x)
{
  print(i)
}
```

```
## [1] "b"
## [1] "r"
## [1] "y"
## [1] "a"
## [1] "n"
## [1] "t"
```

]

---
# Loop through a data frame

.pull-left[

- Loop through variables of a data frame and print the number of missing for each variable

]

.pull-right[

]

---
# Loop through a data frame

.pull-left[

- Loop through variables of a data frame and print the number of missing for each variable

]

.pull-right[

```r
for (i in df)
{ 
  print(sum(is.na(i)))
}
```

]

---
# Loop through a data frame

.pull-left[

- Loop through variables of a data frame and print the number of missing for each variable

]

.pull-right[

```r
for (i in df)
{ 
  print(sum(is.na(i)))
}
```

```
## [1] 0
## [1] 0
## [1] 0
## [1] 0
## [1] 177
## [1] 0
## [1] 0
## [1] 2
```

]

---
# Loop through a data frame

.pull-left[

- Print out the types of variables for each columns in a data frame

]

.pull-right[

]

---
# Loop through a data frame

.pull-left[

- Print out the types of variables for each columns in a data frame

]

.pull-right[

```r
for (i in 1:length(df))
{
  print(class(df[[i]]))
}
```

]

---
# Loop through a data frame

.pull-left[

- Print out the types of variables for each columns in a data frame

]

.pull-right[

```r
for (i in 1:length(df))
{
  print(class(df[[i]]))
}
```

```
## [1] "factor"
## [1] "factor"
## [1] "factor"
## [1] "numeric"
## [1] "numeric"
## [1] "numeric"
## [1] "factor"
```

]

---
class: center, inverse, middle

# Map functions

---
# Map function

.pull-left[

- When you apply the same function to all columns of a data frame,

- you could use a map function in the `purrr` package to make the code simpler

]

.pull-right[

]

---
# Map function

.pull-left[

- When you apply the same function to all columns of a data frame,

- you could use a map function in the `purrr` package to make the code simpler

]

.pull-right[

```r
for (i in 1:length(df))
{
  class(df[[i]])
}
```

- The above is the same as

```r
library(purrr)
map_df(df, class)
```

]

---
# Map function

.pull-left[

- When you apply the same function to all columns of a data frame,

- you could use a map function in the `purrr` package to make the code simpler

]

.pull-right[

- Rewrite the following codes using a `map` function

```r
for (i in 1:length(df))
{
  length(df[[i]])
}
```

]

---
# Map function

.pull-left[

- When you apply the same function to all columns of a data frame,

- you could use a map function in the `purrr` package to make the code simpler

]

.pull-right[

- Rewrite the following codes using a `map` function

```r
for (i in 1:length(df))
{
  length(df[[i]])
}
```

- Rewrite:

```r
library(purrr)
map_df(df, length)
```

]

---
# Map function

.pull-left[

- When you apply the same function to all columns of a data frame,

- you could use a map function in the `purrr` package to make the code simpler

]

.pull-right[

- Rewrite the following codes using a `map` function

```r
for (i in 1:length(df))
{
  mean(df[[i]])
}
```

]

---
# Map function

.pull-left[

- When you apply the same function to all columns of a data frame,

- you could use a map function in the `purrr` package to make the code simpler

]

.pull-right[

- Rewrite the following codes using a `map` function

```r
for (i in 1:length(df))
{
  mean(df[[i]])
}
```

- Rewrite:

```r
library(purrr)
map_df(df, mean)
```

]

---
# Map function

.pull-left[

- When you apply the same function to all columns of a data frame,

- you could use a map function in the `purrr` package to make the code simpler

]

.pull-right[

- Rewrite the following codes using a `map` function

```r
for (i in 1:length(df))
{
  sum(is.na(df[[i]]))
}
```

]

---
# Map function

.pull-left[

- When you apply the same function to all columns of a data frame,

- you could use a map function in the `purrr` package to make the code simpler

]

.pull-right[

- Rewrite the following codes using a `map` function

```r
for (i in 1:length(df))
{
  sum(is.na(df[[i]]))
}
```

- Rewrite:

```r
library(purrr)
map_df(df, ~sum(is.na(.)))
```

]

---
# Map function

.pull-left[

- When you apply the same function to all columns of a data frame,

- you could use a map function in the `purrr` package to make the code simpler

]

.pull-right[

- Rewrite the following codes using a `map` function

```r
for (i in 1:length(df))
{
  sum(is.na(df[[i]]))
}
```

- Rewrite:

```r
library(purrr)
map_df(df, ~sum(is.na(.)))
```

- Notice that `map_df(df, sum(is.na)` would not work because `sum(is.na)` is not a function!

]

---
class: inverse, center, middle

# Write functions with Loop

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- a data frame with all the missing of non-numeric variables replaced by the associated modes.

]

.pull-right[

]

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- a data frame with all the missing of non-numeric variables replaced by the associated modes.

]

.pull-right[

- We use the `mode_impute` function from last class

```r
numeric_impute <- function(d)
{
  for (i in 1:length(d))
  {
      d[[i]] <- mode_impute(d[[i]])
  }
  return(d)
}
```
]
---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- a data frame with all the missing of non-numeric variables replaced by the associated modes.

]

.pull-right[

- We use the `mode_impute` function from last class

```r
numeric_impute <- function(d)
{
  for (i in 1:length(d))
  {
      d[[i]] <- mode_impute(d[[i]])
  }
  return(d)
}
```

- Test the function

```r
colSums(is.na(df))
```

```
## Survived   Pclass      Sex      Age    SibSp     Fare Embarked 
##        0        0        0      177        0        0        2
```

```r
d1 <- numeric_impute(df)
colSums(is.na(d1))
```

```
## Survived   Pclass      Sex      Age    SibSp     Fare Embarked 
##        0        0        0      177        0        0        0
```

]

---
# Map function

.pull-left[

- When you apply the same function to all columns of a data frame,

- you could use a map function in the `purrr` package to make the code simpler

]

.pull-right[

```r
numeric_impute <- function(d)
{
  for (i in 1:length(d))
  {
      d[[i]] <- mode_impute(d[[i]])
  }
  return(d)
}
```

- The above is the same as

```r
numeric_impute <- function(d)
{
  d <- map_df(d, mode_impute)
  return(d)
}
```
]

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- Density plots of all numeric variables.  
]

.pull-right[
]

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- Density plots of all numeric variables.  
]

.pull-right[

```r
density_plot <- function(d)
{
  library(ggplot2)
  for (i in 1:length(d))
  {
    if (is.numeric(d[[i]]))
    {
      print(ggplot(d, aes(x = d[[i]]))+ 
              geom_density()+
              labs(x = names(d)[i]))
    }
  }
}
```

]

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- Density plots of all numeric variables.  
]

.pull-right[

- Test the function

```r
density_plot(df)
```

![](Figs/unnamed-chunk-37-1.png)![](Figs/unnamed-chunk-37-2.png)![](Figs/unnamed-chunk-37-3.png)

]

---
class: inverse, center, middle

# Double Loop

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- all possible the scatter plots.  
]

.pull-right[

]

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- all possible the scatter plots.  
]

.pull-right[

```r
scatter_plot <- function(d)
{
  library(ggplot2)
  l <- length(d)
  for (i in 1:(l-1))
    for (j in (i+1):l)
  {
    if (is.numeric(d[[i]])&is.numeric(d[[j]]))
    {
      print(ggplot(d, aes(x = d[[i]], y = d[[j]]))+ 
              geom_point()+
              labs(x = names(d)[i], y = names(d)[j]))
    }
  }
}
```
]

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- all possible the scatter plots.  
]

.pull-right[

- Test the function

```r
scatter_plot(df)
```

![](Figs/unnamed-chunk-39-1.png)![](Figs/unnamed-chunk-39-2.png)![](Figs/unnamed-chunk-39-3.png)

]

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- all possible the density plots of a numeric variable colored by a non-numeric variable.  
]

.pull-right[
]

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- all possible the density plots of a numeric variable colored by a non-numeric variable.  
]

.pull-right[

```r
density_plot2 <- function(d)
{
  library(ggplot2)
  l <- length(d)
  for (i in 1:(l-1))
    for (j in (i+1):l)
  {
    if (is.numeric(d[[i]])& (!is.numeric(d[[j]])))
    {
      print(ggplot(d, aes(x = d[[i]], color = d[[j]]))+ 
              geom_density()+labs(x = names(d)[i], color = names(d)[j]))
    }
  }
}
```

]

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- all possible the density plots of a numeric variable colored by a non-numeric variable.  
]

.pull-right[

- Test the function

```r
density_plot2(df)
```

]

---
# Test the function

```r
density_plot2(df)
```

![](Figs/unnamed-chunk-43-1.png)![](Figs/unnamed-chunk-43-2.png)![](Figs/unnamed-chunk-43-3.png)

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- all possible the bar plots of a non-numeric variable filled by a non-numeric variable.

]

.pull-right[

```r
bar_plot2 <- function(d)
{
  library(ggplot2)
  l <- length(d)
  for (i in 1:(l-1))
    for (j in (i+1):l)
  {
    if ((!is.numeric(d[[i]])) & (!is.numeric(d[[j]])))
    {
      print(ggplot(d, aes(x = d[[i]], fill = d[[j]])) + 
              geom_bar(position = 'dodge')+
              labs(x = names(d)[i], fill = names(d)[j]))
    }
  }
}
```
]

---
# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- all possible the bar plots of a non-numeric variable filled by a non-numeric variable.

]

.pull-right[

- Test the function

```r
bar_plot2(df)
```

]

---
# Test the function

```r
bar_plot2(df)
```

![](Figs/unnamed-chunk-47-1.png)![](Figs/unnamed-chunk-47-2.png)![](Figs/unnamed-chunk-47-3.png)![](Figs/unnamed-chunk-47-4.png)![](Figs/unnamed-chunk-47-5.png)![](Figs/unnamed-chunk-47-6.png)

---
exclude: true

# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

- all possible the bar plots of a non-numeric variable filled by a non-numeric variable.  
  - all possible the density plots of a numeric variable colored by a non-numeric variable.  
  - all possible the scatter plots.  
]

.pull-right[

]

---
exclude: true

# Example

.pull-left[

Write the following function.  Give an example to test your function.

- Input:

- a data frame

- Output:

.pull-right[

```r
quickplot <- function(d)
{
  density_plot2(d)
  scatter_plot(d)
  bar_plot2(d)
}
```

]

---
# Test the function

```r
df2 <- read_csv('insurance.csv')
quickplot(df2)
```

![](Figs/unnamed-chunk-49-1.png)![](Figs/unnamed-chunk-49-2.png)![](Figs/unnamed-chunk-49-3.png)![](Figs/unnamed-chunk-49-4.png)![](Figs/unnamed-chunk-49-5.png)![](Figs/unnamed-chunk-49-6.png)![](Figs/unnamed-chunk-49-7.png)![](Figs/unnamed-chunk-49-8.png)![](Figs/unnamed-chunk-49-9.png)![](Figs/unnamed-chunk-49-10.png)![](Figs/unnamed-chunk-49-11.png)![](Figs/unnamed-chunk-49-12.png)![](Figs/unnamed-chunk-49-13.png)![](Figs/unnamed-chunk-49-14.png)![](Figs/unnamed-chunk-49-15.png)![](Figs/unnamed-chunk-49-16.png)

---
# Test the function

```r
quickplot(df)
```

![](Figs/unnamed-chunk-50-1.png)![](Figs/unnamed-chunk-50-2.png)![](Figs/unnamed-chunk-50-3.png)![](Figs/unnamed-chunk-50-4.png)![](Figs/unnamed-chunk-50-5.png)![](Figs/unnamed-chunk-50-6.png)![](Figs/unnamed-chunk-50-7.png)![](Figs/unnamed-chunk-50-8.png)![](Figs/unnamed-chunk-50-9.png)![](Figs/unnamed-chunk-50-10.png)![](Figs/unnamed-chunk-50-11.png)![](Figs/unnamed-chunk-50-12.png)