PANDAS数据值框的净现值计算

Question

我在数据框上使用numpy_financial.npv(rate，values)进行净现值计算时出错。

我可以使用数据帧进行净现值计算吗？不确定如何修复此问题。手动遍历每一行？

npvValues =  ['value_1',' value_2', 'value_3', 'value_4', 'value_5', 'RFR']

round(df[npvValues].sample(5),1).sort_index(ascending=False)

DATE        value_1     value_2     value_3     value_4     value_5     RFR             
2017-04-03  38.5        92.8        168.7       257.0       354.0       2.1
2016-01-11  35.7        86.1        156.6       238.7       328.6       2.3
2013-07-29  28.1        67.8        123.3       187.8       258.6       2.3
2011-05-02  24.2        58.3        106.1       161.6       222.5       3.4
2010-01-18  24.4        58.8        107.0       163.0       224.5       3.8

净现值计算

value =  ['value_1',' value_2', 'value_3', 'value_4', 'value_5']

df['NPV_IV'] = npf.npv(rate=df['RFR']/100, values=df[value])
df['NPV_IV']

下面是完整的错误跟踪Full Error Trace

Answer 1

npv中的values参数只接受一维数组，所以你需要遍历它。

df = pd.read_csv('t.csv')

value = ['value_1', 'value_2', 'value_3', 'value_4', 'value_5']

num = df[value].to_numpy()

rate_lists = df['RFR'].tolist()

new_col = []
for index, i in enumerate(num):
    n = npf.npv(rate=rate_lists[index] / 100, values=i)
    new_col.append(n)

df['NPV_IV'] = new_col
print(df)
         DATE  value_1  value_2  value_3  value_4  value_5  RFR      NPV_IV
0  2017-04-03     38.5     92.8    168.7    257.0    354.0  2.1  858.450837
1  2016-01-11     35.7     86.1    156.6    238.7    328.6  2.3  792.491237
2  2013-07-29     28.1     67.8    123.3    187.8    258.6  2.3  623.725804
3  2011-05-02     24.2     58.3    106.1    161.6    222.5  3.4  520.644433
4  2010-01-18     24.4     58.8    107.0    163.0    224.5  3.8  519.488982