DataFrame.applymap(func)
[source]
Apply a function to a Dataframe elementwise.
This method applies a function that accepts and returns a scalar to every element of a DataFrame.
Parameters: |
func : callable Python function, returns a single value from a single value. |
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Returns: |
DataFrame Transformed DataFrame. |
See also
DataFrame.apply
>>> df = pd.DataFrame([[1, 2.12], [3.356, 4.567]]) >>> df 0 1 0 1.000 2.120 1 3.356 4.567
>>> df.applymap(lambda x: len(str(x))) 0 1 0 3 4 1 5 5
Note that a vectorized version of func
often exists, which will be much faster. You could square each number elementwise.
>>> df.applymap(lambda x: x**2) 0 1 0 1.000000 4.494400 1 11.262736 20.857489
But it’s better to avoid applymap in that case.
>>> df ** 2 0 1 0 1.000000 4.494400 1 11.262736 20.857489
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http://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.DataFrame.applymap.html