# dask.dataframe.Series.round

#### Series.round(decimals=0)

Round numeric columns in a DataFrame to a variable number of decimal places.

This docstring was copied from pandas.DataFrame.round.

Some inconsistencies with the Dask version may exist.

Each column can be rounded to a different number of decimal places by
passing a dict or Series mapping column names to the desired precision.
Non-numeric columns are left unchanged.

* **Parameters:**
  **decimals**
  : Number of decimal places to round each column to. If an int is
    given, round each column to the same number of places.
    Otherwise dict and Series round to variable numbers of places.
    Column names should be in the keys if decimals is a
    dict-like, or in the index if decimals is a Series. Any
    columns not included in decimals will be left as is. Elements
    of decimals which are not columns of the input will be
    ignored.

  **\*args**
  : Additional keyword arguments have no effect but might be accepted for
    compatibility with NumPy.
    See [NumPy compatibility kwargs](https://pandas.pydata.org/pandas-docs/stable/user_guide/gotchas.html#gotchas-numpy-kwargs) for more.

  **\*\*kwargs**
  : Additional keyword arguments have no effect but might be accepted for
    compatibility with NumPy.
    See [NumPy compatibility kwargs](https://pandas.pydata.org/pandas-docs/stable/user_guide/gotchas.html#gotchas-numpy-kwargs) for more.
* **Returns:**
  DataFrame
  : A DataFrame with the affected columns rounded to the specified
    number of decimal places.

#### SEE ALSO
[`numpy.around`](https://numpy.org/doc/stable/reference/generated/numpy.around.html#numpy.around)
: Round a numpy array to the given number of decimals.

[`Series.round`](#dask.dataframe.Series.round)
: Round a Series to the given number of decimals.

### Notes

For values exactly halfway between rounded decimal values, pandas rounds
to the nearest even value (e.g. -0.5 and 0.5 round to 0.0, 1.5 and 2.5
round to 2.0, etc.).

### Examples

```pycon
>>> df = pd.DataFrame(
...     [(0.21, 0.32), (0.01, 0.67), (0.66, 0.03), (0.21, 0.18)],
...     columns=["dogs", "cats"],
... )
>>> df
    dogs  cats
0  0.21  0.32
1  0.01  0.67
2  0.66  0.03
3  0.21  0.18
```

By providing an integer each column is rounded to the same number
of decimal places

```pycon
>>> df.round(1)
    dogs  cats
0   0.2   0.3
1   0.0   0.7
2   0.7   0.0
3   0.2   0.2
```

With a dict, the number of places for specific columns can be
specified with the column names as key and the number of decimal
places as value

```pycon
>>> df.round({"dogs": 1, "cats": 0})
    dogs  cats
0   0.2   0.0
1   0.0   1.0
2   0.7   0.0
3   0.2   0.0
```

Using a Series, the number of places for specific columns can be
specified with the column names as index and the number of
decimal places as value

```pycon
>>> decimals = pd.Series([0, 1], index=["cats", "dogs"])
>>> df.round(decimals)
    dogs  cats
0   0.2   0.0
1   0.0   1.0
2   0.7   0.0
3   0.2   0.0
```

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