我有以下数据帧：
ID Model_form A C Actual
1 Exp 2 1.4 4
2 Power model 1 0.2 3
3 Log 0.6 6 7
我正在尝试基于模型形式求解不同的方程：
If model form column contains 'exp' - A*(1-exp(C*actual))
If model form column contains 'pow' - A*(actual^C)
If model form column contains 'log' - A* Ln(1+C*optimal)
目前我正在解决如下问题，
c1 = df['Model_form']].str.contains('exp', flags = re.IGNORECASE)
c2 = df['Model_form']].str.contains('pow', flags = re.IGNORECASE)
c3 = df['Model_form']].str.contains('log', flags = re.IGNORECASE)
df['Actual(y)'] = np.select([c1,c2,c3], [df.eval(df['A']*(1-
np.exp(df['C']*df['Actual'])),df['A']*
(df['Actual']**df['C']),df['A']*np.log(1+df['C']*df['Actual']))])
我得到错误：
eval() takes from 2 to 3 positional arguments but 4 were given
c1 = df['Model_form'].str.contains('exp', flags = re.IGNORECASE)
c2 = df['Model_form'].str.contains('pow', flags = re.IGNORECASE)
c3 = df['Model_form'].str.contains('log', flags = re.IGNORECASE)
labels=[df.eval(df['A']*(1-np.exp(df['C']*df['Actual']))),df.eval("A*(Actual**C)"),df.eval(df['A']*np.log(1+df['C']*df['Actual']))]
最后：
df['Actual(y)']=np.select([c1,c2,c3],labels)
df:的输出
ID Model_form A C Actual Actual(y)
0 1 Exp 2.0 1.44 4 -632.696658
1 2 Power model 1.0 0.20 3.0 1.245731
2 3 Log 0.6 6.00 7.0 2.256720
注意：在第1和第3条件下使用df.eval()没有意义，因为只有df['A']*(1-np.exp(df['C']*df['Actual']))和df['A']*np.log(1+df['C']*df['Actual'])才能提供所需的输出，而df.eval()什么都不做(条件2除外(！！
你得到这个错误：
eval() takes from 2 to 3rd positional arguments but 4 were given
由于第一条件中缺少括号)：
df.eval(df['A']*(1-np.exp(df['C']*df['Actual'])))
^
#added ) parenthesis