如何在for循环中使用lambda函数？

Question

我正在尝试在一些复杂的计算上使用lambda函数。我在数据框中有一个列名“ time_periods_st”，想要创建一些新列，例如：dd1-dd10，z1-z10，z_s1-z_s10。从1到“ time_periods_st”，我们使用一种计算方法（dd1-dd（time_periods_st））；对于“ time_periods_st”，到10，我们使用另一种计算方法（dd（time_periods_st）-dd10）。我们仅受两个不同的time_periods_st值限制（目前为1或5）。

我尝试通过lambda函数使用apply。我的代码正在运行，但数据框为空。

from scipy.stats import norm
import pandas as pd
import math
def delta_dd_cals(df,time_period=10):
    if df['time_periods_st'] == 1:
        for i in range(1,df['time_periods']+1):
                if df['RHO'] > 0:
                    df['dd'+str(i)] = norm.ppf(df['CAST'+str(i-1)]) - norm.ppf(df['CAST'+str(i)])
                    df['z'+str(i)] = df['dd'+str(i)]/math.sqrt(df['RHO'])
                    df['z_s'+str(i)] = (df[['dd'+str(j) for j in range(i+1)]].sum() + df['DD'])/math.sqrt(df['RHO'])
                elif df['RHO']<0 or df['CAST1']<0:
                    df['z'+str(i)] = np.nan
                    df['dd'+str(i)] = np.nan
                    df['z_s'+str(i)] = np.nan
                else:
                    df['z'+str(i)] = 0
                    df['dd'+str(i)] = 0
                    df['z_s'+str(i)] = 0           

        for k in range(df['time_periods_st']+1,time_period+1):
                if df['RHO'] > 0:
                    df['z'+str(k)] = (df['A1'] * (df['Z_NORM']-df['z_s'+str(k-1)])) + ((df['A2'] * df['z'+str(k-1)]))
                    df['dd'+str(k)] = math.sqrt(df['RHO']) * df['z'+str(k)]
                    df['z_s'+str(k)] = (df[['dd'+str(j) for j in range(k+1)]].sum() + df['DD'])/math.sqrt(df['RHO'])

                elif df['RHO']<0 or df['CAST1']<0:
                    df['z'+str(i)] = np.nan
                    df['dd'+str(i)] = np.nan
                    df['z_s'+str(i)] = np.nan
                else:
                    df['z'+str(i)] = 0
                    df['dd'+str(i)] = 0
                    df['z_s'+str(i)] = 0

    else:
        for i in range(1,df['time_periods']+1):
                if df['RHO'] > 0:
                    df['dd'+str(i)] = norm.ppf(df['CAST'+str(i-1)]) - norm.ppf(df['CAST'+str(i)])
                    df['z'+str(i)] = df['dd'+str(i)]/math.sqrt(df['RHO'])
                    df['z_s'+str(i)] = (df[['dd'+str(j) for j in range(i+1)]].sum() + df['DD'])/math.sqrt(df['RHO'])
                elif df['RHO']<0 or df['CAST1']<0:
                    df['z'+str(i)] = np.nan
                    df['dd'+str(i)] = np.nan
                    df['z_s'+str(i)] = np.nan
                else:
                    df['z'+str(i)] = 0
                    df['dd'+str(i)] = 0
                    df['z_s'+str(i)] = 0           

        for k in range(df['time_periods_st']+1,time_period+1):
                if df['RHO'] > 0:
                    df['z'+str(k)] = (df['A1'] * (df['Z_NORM']-df['z_s'+str(k-1)])) + ((df['A2'] * df['z'+str(k-1)]))
                    df['dd'+str(k)] = math.sqrt(df['RHO']) * df['z'+str(k)]
                    df['z_s'+str(k)] = (df[['dd'+str(j) for j in range(k+1)]].sum() + df['DD'])/math.sqrt(df['RHO'])

                elif df['RHO']<0 or df['CAST1']<0:
                    df['z'+str(i)] = np.nan
                    df['dd'+str(i)] = np.nan
                    df['z_s'+str(i)] = np.nan
                else:
                    df['z'+str(i)] = 0
                    df['dd'+str(i)] = 0
                    df['z_s'+str(i)] = 0

df_delta = df_delta.apply(lambda x: delta_dd_cals(x),axis=1)

我的代码正在运行，但数据帧为空。