Methods to Round Values in Pandas DataFrame
There are various ways to Round Values in Pandas DataFrame so let’s see each one by one:
Let’s create a Dataframe with ‘Data Entry’ Column only:
Method 1: Using numpy.round().
Syntax: numpy.round_(arr, decimals = 0, out = None)
Return: An array with all array elements being
rounded off, having same type as input.
This method can be used to round value to specific decimal places for any particular column or can also be used to round the value of the entire data frame to the specific number of decimal places.
Example: Rounding off the value of the “DATA ENTRY” column up to 2 decimal places.
Syntax: Dataframe/Series.apply(func, convert_dtype=True, args=())
Return: Pandas Series after applied function/operation.
Syntax: numpy.ceil(x[, out]) = ufunc ‘ceil’)
Return: An array with the ceil of each element of float data-type.
These methods are used to round values to ceiling value(smallest integer value greater than particular value).
Example: Rounding off the value of a particular column.
Syntax: numpy.floor(x[, out]) = ufunc ‘floor’)
Return: An array with the floor of each element.
These methods are used to round values to floor value(largest integer value smaller than particular value).
Example: Rounding off the value of the “DATA ENTRY” column to its corresponding Floor value.
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