如何通过一次操作截断数据帧的系列/列

Question

There are operations to round or floor or ceiling a column/series of a dataframe but how can one specify the precision for a column and truncate the rest of the values?

df = pd.DataFrame({"a": (1.21233123, 1.2412304498), 'b':(2.11296876, 2.09870989)})

Given this simple data frame, lets say I want to truncate column a and column b to 3 precision without rounding, I simply want to remove the rest of the precision.

 df = pd.DataFrame({"a": (1.212, 1.241), 'b':(2.112, 2.098)})

This would be a result df, there should be a column operation that can be executed but it seems that you can only specify precision for rounding.

Answer 1

You can use round :

In [11]: df.round(3)
Out[11]:
       a      b
0  1.212  2.113
1  1.241  2.099

To "round down" you can subtract 0.001 / 2 from the DataFrame first:

In [12]: (df - 0.0005).round(3)
Out[12]:
       a      b
0  1.212  2.112
1  1.241  2.098

Answer 2

Use numpy.trunc with a bit of trick:

import numpy as np

n_precision = 3
df = np.trunc(df * (10 ** n_precision))/ (10 ** n_precision)
print(df)

       a      b
0  1.212  2.112
1  1.241  2.098

Since np.trunc discards the fractional part, you first multiply numbers by the order of your precision, do np.trunc , divide them back to get the desired output.