在 Pandas 计算中处理除以零
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Handling division by zero in Pandas calculations
提问by Suminda Sirinath S. Dharmasena
I have the following data:
我有以下数据：
a = pd.Series([1, 2, 3])
b = pd.Series([0, 0, 0])
If there is a division by zero I want to in some cases
如果除以零我想在某些情况下
- set the result to one of the series
- set the result to a specific value
- 将结果设置为系列之一
- 将结果设置为特定值
But the following give "unexpected" results:
但以下给出了“意外”的结果：
a.div(b, fill_value = 0)
0 inf
1 inf
2 inf
a.div(b).fillna(0)
0 inf
1 inf
2 inf
a.div(b).combine_first(a)
0 inf
1 inf
2 inf
I want to arrive at:
我想到达：
case 1: set the data to a specific value
情况 1：将数据设置为特定值
0 0
1 0
2 0
case 2: set the value to a specific series
案例 2：将值设置为特定系列
0 1
1 2
2 3
回答by cs95
You can use df.replaceafter division:
您可以df.replace在除法后使用：
(a / b).replace(np.inf, 0)
0 0.0
1 0.0
2 0.0
dtype: float64
(a / b).replace(np.inf, a)
0 1.0
1 2.0
2 3.0
dtype: float64
Want to handle negative infinity too? You'll need:
也想处理负无穷大吗？你需要：
(a / b).replace((np.inf, -np.inf), (a, a))
回答by jezrael
I think you can use Series.replace:
我认为你可以使用Series.replace：
print (a.div(b.replace(0, np.nan)).fillna(0))
0 0.0
1 0.0
2 0.0
dtype: float64
print (a.div(b.replace(0, np.nan)).fillna(a))
0 1.0
1 2.0
2 3.0
dtype: float64
回答by Clock Slave
You can also use the np.isinffunction to check for infinite values and then substitue them with 0. Ex-
您还可以使用该np.isinf函数检查无穷大值，然后将它们替换为 0。例如
a = np.asarray(np.arange(5))
b = np.asarray([1,2,0,1,0])
c = a/b
c[np.isinf(c)] = 0
#result
>>> c
array([ 0. , 0.5, 0. , 3. , 0. ])
