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Remaining stringAsFactor removed. #152

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96 changes: 59 additions & 37 deletions episodes/04-data-structures-part2.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -37,10 +37,10 @@ So far, you have seen the basics of manipulating data frames with our nordic dat

::::::::::::::::::::::::::::::::::::::::: instructor

Pay attention to and explain the errors and warnings generated from the
Pay attention to and explain the errors and warnings generated from the
examples in this episode.

:::::::::::::::::::::::::::::::::::::::::
:::::::::::::::::::::::::::::::::::::::::

```{r, echo=TRUE}
gapminder <- read.csv("data/gapminder_data.csv")
Expand Down Expand Up @@ -70,12 +70,12 @@ gapminder <- read.csv("data/gapminder_data.csv")
your computer. For example,

```{r, eval=FALSE, echo=TRUE}
gapminder <- read.csv("https://datacarpentry.org/r-intro-geospatial/data/gapminder_data.csv", stringsAsFactors = TRUE) #in R version 4.0.0 the default stringsAsFactors changed from TRUE to FALSE. But because below we use some examples to show what is a factor, we need to add the stringAsFactors = TRUE to be able to perform the below examples with factor.
gapminder <- read.csv("https://datacarpentry.org/r-intro-geospatial/data/gapminder_data.csv")
```

- You can read directly from excel spreadsheets without
converting them to plain text first by using the [readxl](https://cran.r-project.org/package=readxl) package.


::::::::::::::::::::::::::::::::::::::::::::::::::

Expand Down Expand Up @@ -193,11 +193,10 @@ gapminder[sample(nrow(gapminder), 5), ]

## Challenge 2

Read the output of `str(gapminder)` again; this time, use what you've learned
about factors and vectors, as well as the output of functions like `colnames`
and `dim` to explain what everything that `str` prints out for `gapminder`
means. If there are any parts you can't interpret, discuss with your
neighbors!
Read the output of `str(gapminder)` again; this time, use what you've learned,
as well as the output of functions like `colnames` and `dim` to explain what
everything that `str` prints out for `gapminder` means. If there are any parts
you can't interpret, discuss with your neighbors!

::::::::::::::: solution

Expand All @@ -219,7 +218,6 @@ We would like to create a new column to hold information on whether the life exp

```{r}
below_average <- gapminder$lifeExp < 70.5
head(gapminder)
```

We can then add this as a column via:
Expand All @@ -228,10 +226,6 @@ We can then add this as a column via:
cbind(gapminder, below_average)
```

```{r, eval=TRUE, echo=FALSE}
head(cbind(gapminder, below_average))
```

We probably don't want to print the entire dataframe each time, so
let's put our `cbind` command within a call to `head` to return
only the first six lines of the output.
Expand Down Expand Up @@ -267,7 +261,7 @@ The sequence `TRUE,TRUE,FALSE` is repeated over all the gapminder rows.
Let's overwrite the content of gapminder with our new data frame.

```{r}
below_average <- as.logical(gapminder$lifeExp<70.5)
below_average <- as.logical(gapminder$lifeExp < 70.5)
gapminder <- cbind(gapminder, below_average)
```

Expand All @@ -279,39 +273,68 @@ gapminder_norway <- rbind(gapminder, new_row)
tail(gapminder_norway)
```

To understand why R is giving us a warning when we try to add this row, let's learn a little more about factors.

## Factors

Here is another thing to look out for: in a `factor`, each different value
represents what is called a `level`. In our case, the `factor` "continent" has 5
levels: "Africa", "Americas", "Asia", "Europe" and "Oceania". R will only accept
values that match one of the levels. If you add a new value, it will become
`NA`.

The warning is telling us that we unsuccessfully added "Nordic" to our
*continent* factor, but 2016 (a numeric), 5000000 (a numeric), 80.3 (a numeric),
49400\.0 (a numeric) and `FALSE` (a logical) were successfully added to
*country*, *year*, *pop*, *lifeExp*, *gdpPercap* and *below\_average*
respectively, since those variables are not factors. 'Norway' was also
successfully added since it corresponds to an existing level. To successfully
add a gapminder row with a "Nordic" *continent*, add "Nordic" as a *level* of
the factor:
represents what is called a `level`.

Let's convert the columns continent and country into factors:

```{r}
gapminder$continent <- factor(gapminder$continent)
gapminder$country <- factor(gapminder$country)
str(gapminder)
```

In our case, the `factor` "continent" has 5 levels: "Africa", "Americas",
"Asia", "Europe" and "Oceania":

```{r}
levels(gapminder$continent)
```

A factor is not a character. For example, if we try to add the same row from
above to our data.frame, some values will become `NA`. This is so because
"continent" and "country" are now factors and R will only accept new values
that match one of the factor's levels:

```{r}
new_row <- list('Norway', 2016, 5000000, 'Nordic', 80.3, 49400.0, FALSE)
gapminder_norway <- rbind(gapminder, new_row)
```

This warning is telling us that we unsuccessfully added "Nordic" to our
*continent* factor (see below), but 2016 (a numeric), 5000000 (a numeric), 80.3
(a numeric), 49400\.0 (a numeric) and `FALSE` (a logical) were successfully
added to *country*, *year*, *pop*, *lifeExp*, *gdpPercap* and *below\_average*
respectively, since those variables are not factors. 'Norway' was also
successfully added since it corresponds to an existing level.

```{r}
tail(gapminder_norway, n = 1)
```

To successfully add a row with a "Nordic" *continent*, add "Nordic" as a
*level* of the factor:

```{r}
levels(gapminder$continent) <- c(levels(gapminder$continent), "Nordic")
```

And then add the Norway row again:

```{r}
gapminder_norway <- rbind(gapminder,
list('Norway', 2016, 5000000, 'Nordic', 80.3,49400.0, FALSE))
tail(gapminder_norway)
list('Norway', 2016, 5000000, 'Nordic', 80.3,49400.0, FALSE))
tail(gapminder_norway, n = 1)
```

Alternatively, we can change a factor into a character vector; we lose the handy
categories of the factor, but we can subsequently add any word we want to the
column without babysitting the factor levels:
Alternatively, we can change the "continent" factor into a character vector. In
this way, we lose the handy categories of the factor, but we can subsequently
add any word we want to the column without babysitting the factor levels:

```{r}
str(gapminder)
gapminder$continent <- as.character(gapminder$continent)
str(gapminder)
```
Expand All @@ -324,7 +347,7 @@ vectors and rows are lists.* We can also glue two data frames together with

```{r}
gapminder <- rbind(gapminder, gapminder)
tail(gapminder, n=3)
tail(gapminder, n = 3)
```

But now the row names are unnecessarily complicated (not consecutive numbers).
Expand Down Expand Up @@ -386,4 +409,3 @@ df <- cbind(df, coffeetime = c(TRUE, TRUE))

::::::::::::::::::::::::::::::::::::::::::::::::::


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