modin.pandas.DataFrame.round¶

DataFrame.round(decimals=0, *args, **kwargs)[source]¶

Round a DataFrame to a variable number of decimal places.

Parameters:

• decimals (int, dict, Series) – 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 keywords have no effect but might be accepted for compatibility with numpy.

• **kwargs – Additional keywords have no effect but might be accepted for compatibility with numpy.

Returns:

A DataFrame with the affected columns rounded to the specified number of decimal places.

Return type:

DataFrame

See also

numpy.around

Round a numpy array to the given number of decimals.

Series.round

Round a Series to the given number of decimals.

Examples

>>> df = pd.DataFrame([(.21, .32), (.01, .67), (.66, .03), (.21, .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

Copy

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

>>> 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

Copy

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

>>> 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

Copy