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pythonpandasmathrounding

Round a series to N number of significant figures

I have a dataframe of floats and I need make a function that will take a column and round all the values to N number of significant figures

So the column might look something like: 

123.949
23.87 
1.9865
0.0129500

and if I wanted to round to 3 significant figures I would pass the column and 3 to the function to get this 

124.0
23.9
1.99
0.013

How can I do this efficiently without looping through the column?

I have an equation that will calculate the significant figures for a number

round(x, N-int(floor(log10(abs(x))))

but it doesn't work on a series or dataframe

Solution

  • You can use, pandas.Series.apply which implements a function element wise across an axis (column or row):

    df.col.apply(lambda x: round(x, N - int(floor(log10(abs(x))))))

    Note that you can't really use pandas.DataFrame.apply here since the round function should be element wise, not on the entire axis.

    The difference would be that your function input is float instead of getting an array.

    Another option would be applymap which implements a function element-wise on the entire pandas.DataFrame.

    df.applymap(lambda x: round(x, N - int(floor(log10(abs(x))))))