大熊猫,numpy向下舍入到最近的100

Question

我使用下面的代码创建了一个数据框列,并试图弄清楚如何将其舍入到最近的100.

...
# This prints out my new value rounded to the nearest whole number.    
df['new_values'] = (10000/df['old_values']).apply(numpy.floor)

# How do I get it to round down to the nearest 100th instead?
# i.e. 8450 rounded to 8400

Answer 1

借用 @jezrael 的示例数据框

df = pd.DataFrame({'old_values':[8450, 8470, 343, 573, 34543, 23999]})

使用floordiv或//

df // 100 * 100

   old_values
0        8400
1        8400
2         300
3         500
4       34500
5       23900

Answer 2

你需要除以100,转换为int和持续多个100:

df['new_values'] = (df['old_values'] / 100).astype(int) *100

与...一样:

df['new_values'] = (df['old_values'] / 100).apply(np.floor).astype(int) *100

样品:

df = pd.DataFrame({'old_values':[8450, 8470, 343, 573, 34543, 23999]})
df['new_values'] = (df['old_values'] / 100).astype(int) *100
print (df)
   old_values  new_values
0        8450        8400
1        8470        8400
2         343         300
3         573         500
4       34543       34500
5       23999       23900

编辑:

df = pd.DataFrame({'old_values':[3, 6, 89, 573, 34, 23]})
#show output of first divide for verifying output
df['new_values1'] = (10000/df['old_values'])
df['new_values'] = (10000/df['old_values']).div(100).astype(int).mul(100)
print (df)
   old_values  new_values1  new_values
0           3  3333.333333        3300
1           6  1666.666667        1600
2          89   112.359551         100
3         573    17.452007           0
4          34   294.117647         200
5          23   434.782609         400