Load data from txt-CodePudding

I am loading a txt file containig complex number. The data are formatted in this way enter image description here

How can I create a two separate arrays, one for the real part and one for the immaginary part?

I tried to create a panda dataframe using e-01 as a separator but in this way I loose this info

CodePudding user response：

df = pd.read_fwf(r'c:\test\complex.txt', header=None)
df[['real','im']] = df[0].str.extract(r'\(([-.\de] )([ -]\d\.[\de\-j] )')
print(df)

                                                    0                       real                          im
0   (9.486832980505137680e-01-3.162277660168379412...   9.486832980505137680e-01  -3.162277660168379412e-01j
1   (9.486832980505137680e-01 9.486832980505137680...   9.486832980505137680e-01   9.486832980505137680e-01j
2   (-9.486832980505137680e-01 9.48683298050513768...  -9.486832980505137680e-01   9.486832980505137680e-01j
3   (-3.162277660168379412e-01 3.16227766016837941...  -3.162277660168379412e-01   3.162277660168379412e-01j
4   (-3.162277660168379412e-01 9.48683298050513768...  -3.162277660168379412e-01   9.486832980505137680e-01j
5   (9.486832980505137680e-01-3.162277660168379412...   9.486832980505137680e-01  -3.162277660168379412e-01j
6   (-3.162277660168379412e-01 3.16227766016837941...  -3.162277660168379412e-01   3.162277660168379412e-01j
7   (9.486832980505137680e-01-9.486832980505137680...   9.486832980505137680e-01  -9.486832980505137680e-01j
8   (9.486832980505137680e-01-9.486832980505137680...   9.486832980505137680e-01  -9.486832980505137680e-01j
9   (-3.162277660168379412e-01 3.16227766016837941...  -3.162277660168379412e-01   3.162277660168379412e-01j
10  (3.162277660168379412e-01-9.486832980505137680...   3.162277660168379412e-01  -9.486832980505137680e-01j

CodePudding user response：

Never knew how annoyingly involved it is to read complex numbers with Pandas, This is a slightly different solution than @Алексей's. I prefer to avoid regular expressions when not absolutely necessary.

# Read the file, pandas defaults to string type for contents
df = pd.read_csv('complex.txt', header=None, names=['string'])

# Convert string representation to complex.
# Use of `eval` is ugly but works.
df['complex'] = df['string'].map(eval)

# Alternatively...
#df['complex'] = df['string'].map(lambda c: complex(c.strip('()')))

# Separate real and imaginary parts
df['real'] = df['complex'].map(lambda c: c.real)
df['imag'] = df['complex'].map(lambda c: c.imag)

df

is...

                                              string             complex  \
0  (9.486832980505137680e-01-3.162277660168379412...  0.948683-0.316228j   
1  (9.486832980505137680e-01 9.486832980505137680...  0.948683 0.948683j   
2  (-9.486832980505137680e-01 9.48683298050513768... -0.948683 0.000000j   
3  (-3.162277660168379412e-01 3.16227766016837941... -0.316228 0.316228j   
4  (-3.162277660168379412e-01 9.48683298050513768... -0.316228 0.948683j   
5  (9.486832980505137680e-01-3.162277660168379412...  0.948683-0.316228j   
6  (3.162277660168379412e-01 3.162277660168379412...  0.316228 0.316228j   
7  (9.486832980505137680e-01-9.486832980505137680...  0.948683-0.948683j   

       real           imag  
0  0.948683  -3.162278e-01  
1  0.948683   9.486833e-01  
2 -0.948683   9.486833e-01  
3 -0.316228   3.162278e-01  
4 -0.316228   9.486833e-01  
5  0.948683  -3.162278e-01  
6  0.316228   3.162278e-01  
7  0.948683  -9.486833e-01

df.dtypes

prints out..

string         object
complex    complex128
real          float64
imag          float64
dtype: object