python - 如何使用列值计算方程并使用python将输出值存储在另一个之下？

Question

我有一个数据集，其列值将用于方程式。 Max angle是用户定义的，角度增量Ang将是角度步长。

假设 Max Angle = 30 ， Angular Increment = 10，所以我想要每个输入行有 4 个输出行。只有角度必须随方程中的 0、10、20、30 变化。

第一列是我的索引“ID”。我的数据集由 300 行组成。所以我的最终输出必须有 300*4（角度步长）行。

样本数据集：

编辑数据集：

data ='''
ID,1,2,3
23,0.88905321,0.500807892,0.499545029
105,0.334209544,0.24077062,0.345252261
47,0.020669404,0.154582048,0.044395524
28,0.07913145,0.987645061,0.421184162
23,0.5654544,0.879541062,0.456556261
105,0.45678404,0.789546214,0.456217524

import pandas as pd
import numpy as np
from math import *

data ='''
ID,1,2,3
23,0.88905321,0.500807892,0.499545029
105,0.334209544,0.24077062,0.345252261
47,0.020669404,0.154582048,0.044395524
28,0.07913145,0.987645061,0.421184162
'''
df = pd.read_csv(io.StringIO(data),index_col=0)
M = df.iloc[:,:]

#suppose
Max_ang = 30
Ang = 10

#Equation:
solution = 0.88905321*cos(Ang*(pi/180)) + 0.500807892*sin(Ang*(pi/180)) + 0.499545029 * sin(Ang*(pi/180))*cos(Ang*(pi/180))

方程：

解 = Column1_val x cos(Ang x (pi/180)) + Column2_val x sin(Ang x (pi/180)) + Column3_val x sin(Ang x (pi/180)) x cos(Ang x (pi/180) )

预期输出：

标签： pythonpandaslistnumpy

Answer 1

这里不需要for loopwith iterrows，这会很慢。

这是一个使用numpy broadcasting.

reindex首先，我们使用and获取正确格式的数据框index.repeat：

import numpy as np

Max_ang = 30
Ang = 10
Angels = np.arange(0,Max_ang+Ang,step=Ang).tolist()

df = df.reindex(df.index.repeat(len(Angels)))
df['Ang'] = Angels * df.index.nunique()

pi_div_180 = np.pi/180

df['new'] = \
df['1'] * np.cos(df['Ang'] * pi_div_180) + \
df['2'] * np.sin(df['Ang'] * pi_div_180) + \
df['3'] * np.sin(df['Ang'] * pi_div_180) * np.cos(df['Ang']*pi_div_180)

输出

            1         2         3  Ang       new
ID                                              
23   0.889053  0.500808  0.499545    0  0.889053
23   0.889053  0.500808  0.499545   10  1.047938
23   0.889053  0.500808  0.499545   20  1.167274
23   0.889053  0.500808  0.499545   30  1.236656
105  0.334210  0.240771  0.345252    0  0.334210
105  0.334210  0.240771  0.345252   10  0.429983
105  0.334210  0.240771  0.345252   20  0.507365
105  0.334210  0.240771  0.345252   30  0.559318
47   0.020669  0.154582  0.044396    0  0.020669
47   0.020669  0.154582  0.044396   10  0.054790
47   0.020669  0.154582  0.044396   20  0.086562
47   0.020669  0.154582  0.044396   30  0.114415
28   0.079131  0.987645  0.421184    0  0.079131
28   0.079131  0.987645  0.421184   10  0.321459
28   0.079131  0.987645  0.421184   20  0.547520
28   0.079131  0.987645  0.421184   30  0.744730

要删除不必要的列，请使用df.filter：

df = df.filter(regex='\D')

     Ang       new
ID                
23     0  0.889053
23    10  1.047938
23    20  1.167274
23    30  1.236656
105    0  0.334210
105   10  0.429983
105   20  0.507365
105   30  0.559318
47     0  0.020669
47    10  0.054790
47    20  0.086562
47    30  0.114415
28     0  0.079131
28    10  0.321459
28    20  0.547520
28    30  0.744730