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.

6 Ways of Subsetting Data in R

- Subset Using Brackets by Selecting Rows and Columns. ...
- Subset Using Brackets by Excluding Rows and Columns. ...
- Subset Using Brackets with which() Function. ...
- Subset Data with subset() Function. ...
- Subset Data in Combination of select() and filter() Functions. ...
- Subset a Random Sample with sample() Function.

When you are choosing an expression vector, you'd better keep these things in mind:

- Expression System. You need to choose an expression vector that is specific for the expression system. ...
- Purification Tag. ...
- Applications of the Target Protein. ...
- Strength of the Promoter. ...
- Selectable Marker. ...
- Vector Size.

You can subset a column in R in different ways:

- If you want to subset just one column, you can use single or double square brackets to specify the index or the name (between quotes) of the column.
- Specifying the indices after a comma (leaving the first argument blank selects all rows of the data frame).

There are three operators that can be used to extract subsets of R objects.

- The [ operator always returns an object of the same class as the original. ...
- The [[ operator is used to extract elements of a list or a data frame. ...
- The $ operator is used to extract elements of a list or data frame by literal name.

In set theory, a subset is denoted by the symbol ⊆ and read as 'is a subset of'. Using this symbol we can express subsets as follows: A ⊆ B; which means Set A is a subset of Set B.

In this tutorial, we introduce how to filter a data frame rows using the dplyr package:

- Filter rows by logical criteria: my_data %>% filter(Sepal. ...
- Select n random rows: my_data %>% sample_n(10)
- Select a random fraction of rows: my_data %>% sample_frac(10)
- Select top n rows by values: my_data %>% top_n(10, Sepal.

Select Data Frame Columns in R

- pull(): Extract column values as a vector. ...
- select(): Extract one or multiple columns as a data table. ...
- select_if(): Select columns based on a particular condition. ...
- Helper functions - starts_with(), ends_with(), contains(), matches(), one_of(): Select columns/variables based on their names.

Select a Subset of a Dataframe using the Indexing Operator

- Selecting Only Columns. To select a column using indexing operator use the following line of code. housing[ 'population' ] ...
- Selecting Rows. You can use the indexing operator to select specific rows based on certain conditions.

Extract data frame cell value

- Extract value of a single cell: df_name[x, y] , where x is the row number and y is the column number of a data frame called df_name .
- Extract the entire row: df_name[x, ] , where x is the row number. ...
- Extract the entire column: df_name[, y] where y is the column number.

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