Python 使用最大值和最小值优化数据框中的循环

Question

我有疑问如何优化我的代码，实际上只有循环。我用来计算最多两行的解决方案，有时最多计算行数。

我尝试使用 .loc 和 .clip 更改我的代码，但是当它多次出现关于 max 或 min 时，我在逻辑表达式方面遇到了一些麻烦。

它在看开头：

def Calc(row):
    if row['Forecast'] == 0:
        return max(row['Qty'],0)
    elif row['def'] == 1:
         return 0
    elif row['def']  == 0:
        return round(max(row['Qty'] - ( max(row['Forecast_total']*14,(row['Qty_12m_1']+row['Qty_12m_2'])) * max(1, (row['Total']/row['Forecast'])/54)),0 ))

df['Calc'] = df.apply(Calc, axis=1)

我设法使用我指出的函数来更改它，但是我在如何编写这个 max(max())

时遇到了问题

df.loc[(combined_sf2['Forecast'] == 0),'Calc'] = df.clip(0,None)
df.loc[(combined_sf2['def'] == 1),'Calc'] = 0
df.loc[(combined_sf2['def'] == 0),'Calc'] = round(max(df['Qty']- (max(df['Forecast_total']
                                                                      *14,(df['Qty_12m_1']+df['Qty_12m_2']))
                                                                      *max(1, (df['Total']/df['Forecast'])/54)),0))

前两个功能有效，最后一个无效。

id  Forecast    def Calc        Qty Forecast_total  Qty_12m_1   Qty_12m_2   Total
31551   0       0   0            2        0             0       0             95
27412   0,1     0   1            3        0,1           11      0              7
23995   0,1     0   0            4        0             1       0              7
27411   5,527   1   0,036186    60       0,2            64      0             183
28902   5,527   0   0,963814    33       5,327          277     0             183
23954   5,527   0   0            6        0             6       0             183
23994   5,527   0   0            8        0             0       0             183
31549   5,527   0   0            6        0             1       0             183
31550   5,527   0   0            6        0             10      0             183

Answer 1

使用numpy.select and instead max use numpy.maximum:

m1 = df['Forecast'] == 0
m2 = df['def'] == 1
m3 = df['def'] == 0

s1 = df['Qty'].clip(lower=0)
s3 = round(np.maximum(df['Qty'] - (np.maximum(df['Forecast_total']*14,(df['Qty_12m_1']+df['Qty_12m_2'])) * np.maximum(1, (df['Total']/df['Forecast'])/54)),0 ))

df['Calc2'] = np.select([m1, m2, m3], [s1, 0, s3], default=None)

Python 使用最大值和最小值优化数据框中的循环

Python optimization of loop in data frame with max and min values

optimization

max

dataframe

pandas

pandas-loc