我有一个 pandas 数据框，其中某些列具有数值，而其他列则没有，如下所示:
City a b c
Detroit 129 0.54 2,118.00
East 188 0.79 4,624.4712
Houston 154 0.65 3,492.1422
Los Angeles 266 1.00 7,426.00
Miami 26 0.11 792.18
MidWest 56 0.24 772.7813
我想将这些数值四舍五入到小数点后两位，我正在使用:
df = df.replace(np.nan, '', regex=True)
之后 df 变为:
City a b c
Detroit 129.0 0.54 2,118.0
East 188.0 0.79 4,624.47
Houston 154.0 0.65 3,492.14
Los Angeles 266.0 1.0 7,426.0
Miami 26.0 0.11 792.18
MidWest 56.0 0.24 772.78
它大部分工作正常，但它也会将适当的整数转换为小数，即像 100 这样的值四舍五入为 100.0。我想要这样的数据框:
City a b c
Detroit 129 0.54 2,118
East 188 0.79 4,624.47
Houston 154 0.65 3,492.14
Los Angeles 266 1 7,426
Miami 26 0.11 792.18
MidWest 56 0.24 772.28
我想将这些值本身保留为适当的整数，同时在所有数字列中将其他值四舍五入到小数点后两位。我怎样才能做到这一点？
最佳答案
使用g format :
General format. For a given precision p >= 1, this rounds the number to p significant digits and then formats the result in either fixed-point format or in scientific notation, depending on its magnitude.
The precise rules are as follows: suppose that the result formatted with presentation type 'e' and precision p-1 would have exponent exp. Then if -4 <= exp < p, the number is formatted with presentation type 'f' and precision p-1-exp. Otherwise, the number is formatted with presentation type 'e' and precision p-1. In both cases insignificant trailing zeros are removed from the significand, and the decimal point is also removed if there are no remaining digits following it, unless the '#' option is used.
Positive and negative infinity, positive and negative zero, and nans, are formatted as inf, -inf, 0, -0 and nan respectively, regardless of the precision.
A precision of 0 is treated as equivalent to a precision of 1. The default precision is 6.
df.update(df.select_dtypes(include=np.number).applymap('{:,g}'.format))
print (df)
City a b c
0 Detroit 129 0.54 2,118
1 East 188 0.79 4,624.47
2 Houston 154 0.65 3,492.14
3 Los Angeles 266 1 7,426
4 Miami 26 0.11 792.18
5 MidWest 56 0.24 772.781
关于python-3.x - 如果小数为 0，Pandas 将 float 转换为 int，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/58166923/