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# PySpark SQL Functions | round method

schedule Aug 12, 2023
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PySpark SQL Functions' `round(~)` method rounds the values of the specified column.

# Parameters

1. `col` | `string` or `Column`

The column to perform rounding on.

2. `scale` | `int` | `optional`

If scale is positive, such as `scale=2`, then values are rounded to the nearest 2nd decimal. If scale is negative, such as `scale=-1`, then values are rounded to the nearest tenth. By default, `scale=0`, that is, values are rounded to the nearest integer.

# Return Value

A PySpark Column (`pyspark.sql.column.Column`).

# Examples

Consider the following PySpark DataFrame:

``` df = spark.createDataFrame([["Alex", 90.4], ["Bob", 100.5], ["Cathy", 100.63]], ["name", "salary"])df.show() +-----+------+| name|salary|+-----+------+| Alex| 90.4|| Bob| 100.5||Cathy|100.63|+-----+------+ ```

## Rounding column values to the nearest integer

To round to the nearest integer:

``` import pyspark.sql.functions as Fdf.select(F.round("salary")).show() +----------------+|round(salary, 0)|+----------------+| 90.0|| 101.0|| 101.0|+----------------+ ```

Notice how `100.5` got rounded up to `101`.

## Rounding column values to the nearest first decimal

To round to the nearest 1st decimal:

``` df.select(F.round("salary", scale=1)).show() +----------------+|round(salary, 1)|+----------------+| 90.4|| 100.5|| 100.6|+----------------+ ```

## Rounding column values to the nearest tenth

To round to the nearest tenth:

``` df.select(F.round("salary", scale=-1)).show() +-----------------+|round(salary, -1)|+-----------------+| 90.0|| 100.0|| 100.0|+-----------------+ ```
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