# How do you spread data in R?

## How do you spread data in R?

To use spread() , pass it the name of a data frame, then the name of the key column in the data frame, and then the name of the value column. Pass the column names as they are; do not use quotes. To tidy table2 , you would pass spread() the key column and then the value column.

**What package is spread in in r?**

The spread() function from the tidyr package can be used to “spread” a key-value pair across multiple columns.

**What is a spread key?**

key is the column whose values will become variable names. value is the column where values will fill in under the new variables created from key .

### How do you reshape data from long to wide in R?

Reshape from long to wide in R is also achieved using spread() and cast() function.

- Reshape from wide to long using reshape(), gather() and melt() function.
- Reshape from long to wide using reshape(), spread() and dcast() function.

**How do I separate column data in R?**

Split Column Into Two Columns in R

- Use the separate Function to Split Column Into Two Columns in R.
- Use the extract Function to Split Column Into Two Columns in R.
- Use the str_split_fixed Function to Split Column Into Two Columns in R.

**What is tidy format in R?**

Tidy data is a standard way of mapping the meaning of a dataset to its structure. A dataset is messy or tidy depending on how rows, columns and tables are matched up with observations, variables and types. In tidy data: Every column is a variable. Every row is an observation.

#### How many main components are in Gather () function?

There are four fundamental functions of data tidying: gather() takes multiple columns, and gathers them into key-value pairs: it makes “wide” data longer. spread() takes two columns (key & value) and spreads in to multiple columns, it makes “long” data wider. separate() splits a single column into multiple columns.

**What is Tidyr package in R?**

tidyr is new package that makes it easy to “tidy” your data. Tidy data is data that’s easy to work with: it’s easy to munge (with dplyr), visualise (with ggplot2 or ggvis) and model (with R’s hundreds of modelling packages). The two most important properties of tidy data are: Each column is a variable.

**What is long and wide format in R?**

When there are multiple measurements of the same subject, across time or using different tools, the data is often described as being in “wide” format if there is one observation row per subject with each measurement present as a different variable and “long” format if there is one observation row per measurement (thus.

## How do I subset columns in R?

So, to recap, here are 5 ways we can subset a data frame in R:

- Subset using brackets by extracting the rows and columns we want.
- Subset using brackets by omitting the rows and columns we don’t want.
- Subset using brackets in combination with the which() function and the %in% operator.
- Subset using the subset() function.

**How does split work in R?**

The split() is a built-in R function that divides the Vector or data frame into the groups defined by the function. It accepts the vector or data frame as an argument and returns the data into groups. The unsplit() function in R does the reverse of the split() function.

**What do you need to know about spread function?**

In order to do this we need to learn about the spread () function: data is your dataframe of interest. key is the column whose values will become variable names. value is the column where values will fill in under the new variables created from key. If we consider piping, we can write this as:

### What does spread ( ) do in Table 2?

With spread () it does similar to what you would expect. We have a data frame where some of the rows contain information that is really a variable name. This means the columns are a combination of variable names as well as some data. The picture below displays this: We can consider the following data which is table 2:

**Are there any data processing functions in R?**

Although many fundamental data processing functions exist in R, they have been a bit convoluted to date and have lacked consistent coding and the ability to easily flow together. This leads to difficult-to-read nested functions and/or choppy code.

**How is the spread function used in tidyr?**

The spread () function from the tidyr package can be used to “spread” a key-value pair across multiple columns. This function uses the following basic syntax: spread (data, key value)