[英]Iterating through rows of a dataframe to fill column in python
我有以下数据框(称为 data_coh):
roi mag phase coherence
0 1 0.699883 0.0555903 NaN
1 2 0.640482 0.1053 NaN
2 3 0.477865 1.14926 NaN
3 4 0.128119 2.28403 NaN
4 5 0.563046 2.53091 NaN
5 6 0.58869 0.94647 NaN
6 7 0.428383 1.13915 NaN
7 8 0.164036 1.95959 NaN
8 9 0.27912 3.07456 NaN
9 10 0.244237 2.78111 NaN
10 11 0.696592 2.61011 NaN
11 12 0.237346 3.01836 NaN
对于每一行,我想计算其相干值如下(注意我想使用虚数单位j):
import math
import cmath
for roin, val in enumerate(data_coh):
data_coh.loc[roin,'coherence'] = mag*math.cos(phase) + mag*math.sin(phase)*j
首先,它无法执行计算(基于幅度和相位计算复数)。 J 是一个复数单位(来自 cmath)。 但另外,即使 j 被排除在外,对行的分配也没有正确完成。 为什么会这样,如何纠正?
无需迭代或导入math
或cmath
,只需 pandas 和 numpy:
import pandas as pd
import numpy as np
df['coherence'] = df['mag'] * (np.cos(df['phase']) + 1j*df['phase'])
# Result
df
roi mag phase coherence
0 1 0.699883 0.05559 0.698802+0.038907j
1 2 0.640482 0.10530 0.636934+0.067443j
2 3 0.477865 1.14926 0.195525+0.549191j
3 4 0.128119 2.28403 -0.083826+0.292628j
4 5 0.563046 2.53091 -0.461279+1.425019j
5 6 0.588690 0.94647 0.344119+0.557177j
6 7 0.428383 1.13915 0.179221+0.487992j
7 8 0.164036 1.95959 -0.062182+0.321443j
8 9 0.279120 3.07456 -0.278493+0.858171j
9 10 0.244237 2.78111 -0.228539+0.67925j
10 11 0.696592 2.61011 -0.600502+1.818182j
11 12 0.237346 3.01836 -0.235546+0.716396j
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