Python 初始化空的 Pandas 系列并有条件地添加到其中
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Initialize empty Pandas series and conditionally add to it
提问by Gaurav Bansal
I have a pandas DataFrame named Xas shown below.
我有一个X如下所示的Pandas DataFrame 。
X = pd.DataFrame({
'month_1': [1, 0, 0, 0, 0],
'month_2': [0, 1, 0, 0, 0],
'age': [1, 2, 3, 4, 5]
})
months = X['month_1'] + X['month_2']
age = X['age']
I want to create an equation that adds up series from Xbased on whether that term from keepis True or False. The code below works.
我想创建一个方程式，X根据该术语keep是 True 还是 False ，将系列相加。下面的代码有效。
keep={'seasonality':True, 'age':True}
equation = months
if keep['age']:
equation = equation + age
print(equation)
0 2
1 3
2 3
3 4
4 5
dtype: int64
However, I can't get it to work if I initialize equationwith an empty series and then add terms based on keep. When I try to do this I get NaN values. How can I do this?
但是，如果我equation使用空系列进行初始化，然后基于keep. 当我尝试这样做时，我得到 NaN 值。我怎样才能做到这一点？
keep={'seasonality':True, 'age':True}
equation = pd.Series([])
if keep['seasonality']:
equation = equation + months
if keep['age']:
equation = equation + age
print(equation)
0 NaN
1 NaN
2 NaN
3 NaN
4 NaN
dtype: float64
回答by YOBEN_S
If I understand correctly , you can using add+ fill_value=0
如果我理解正确，您可以使用add+fill_value=0
equation = pd.Series([])
if keep['seasonality']:
equation = equation.add(months,fill_value=0)
if keep['age']:
equation = equation.add(age,fill_value=0)
equation
Out[91]:
0 2.0
1 3.0
2 3.0
3 4.0
4 5.0
dtype: float64
