Question

我正在尝试使用lambda函数将列值与浮点值相乘，但是会引发异常。

代码段：

m_forecasts['potential'] = m_forecasts['bnchmk_qty'].apply(lambda x: x * round((m_uio + 1) / (b_uio + 1)))

错误：

line 374, in <lambda>   
m_forecasts['potential'] = m_forecasts['bnchmk_qty'].apply(lambda x: x * round((m_uio + 1) / (b_uio + 1)))
TypeError: unsupported operand type(s) for *: 'function' and 'float')

该错误的根本原因是什么？请帮忙。

注意：正在使用熊猫0.17版本

head() of bnchmk_qty column:
0    <function multiplier at 0x1135ae230>
1    <function multiplier at 0x1135ae230>
2    <function multiplier at 0x1135ae230>
3    <function multiplier at 0x1135ae230>
4    <function multiplier at 0x1135ae230>
Name: bnchmk_qty, dtype: object

Answer 1

对我来说，它工作得很好，但是最好省略apply，因为在幕后循环：

m_forecasts = pd.DataFrame({'bnchmk_qty': [4.5,7.8,43.7]})

m_uio = 10.5
b_uio = 4.8
m_forecasts['potential'] = m_forecasts['bnchmk_qty'] * round((m_uio + 1) / (b_uio + 1))
print (m_forecasts)
   bnchmk_qty  potential
0         4.5        9.0
1         7.8       15.6
2        43.7       87.4

我测试代码生成函数列：

df = pd.DataFrame({'quantity': {pd.Timestamp('2011-01-31 00:00:00'): 32.21, pd.Timestamp('2011-02-28 00:00:00'): 28.32, pd.Timestamp('2011-03-31 00:00:00'): 27.12, pd.Timestamp('2011-04-30 00:00:00'): 29.56, pd.Timestamp('2011-05-31 00:00:00'): 31.98, pd.Timestamp('2011-06-30 00:00:00'): 26.25, pd.Timestamp('2011-07-31 00:00:00'): 24.75, pd.Timestamp('2011-08-31 00:00:00'): 25.56, pd.Timestamp('2011-09-30 00:00:00'): 26.68, pd.Timestamp('2011-10-31 00:00:00'): 29.12, pd.Timestamp('2011-11-30 00:00:00'): 33.87, pd.Timestamp('2011-12-31 00:00:00'): 35.45}})

print (df)
            quantity
2011-01-31     32.21
2011-02-28     28.32
2011-03-31     27.12
2011-04-30     29.56
2011-05-31     31.98
2011-06-30     26.25
2011-07-31     24.75
2011-08-31     25.56
2011-09-30     26.68
2011-10-31     29.12
2011-11-30     33.87
2011-12-31     35.45

import statsmodels.api as sm  

p,d,q = 0,0,0
model = sm.tsa.ARIMA(endog=df['quantity'].astype(float), order=(p, d, q)).fit() ; 
fsales = model.forecast(12)[0]
print (fsales)
[29.23916666 29.23916666 29.23916666 29.23916666 29.23916666 29.23916666
 29.23916666 29.23916666 29.23916666 29.23916666 29.23916666 29.23916666]

df['Forecast'] = fsales
print (df)
            quantity   Forecast
2011-01-31     32.21  29.239167
2011-02-28     28.32  29.239167
2011-03-31     27.12  29.239167
2011-04-30     29.56  29.239167
2011-05-31     31.98  29.239167
2011-06-30     26.25  29.239167
2011-07-31     24.75  29.239167
2011-08-31     25.56  29.239167
2011-09-30     26.68  29.239167
2011-10-31     29.12  29.239167
2011-11-30     33.87  29.239167
2011-12-31     35.45  29.239167

print(sm.version.version)
'0.8.0'

*：'函数'和'浮点数'不支持的操作数类型

1 个答案: