Numpy Array, Data must be 1-dimensional

Question

I am attempting to reproduce MatLab code in Python and am stumbling with a MatLab matrix. The block of code in MatLab is below:

for i = 1:Np
    y = returns(:,i);
    sgn = modified_sign(y); 
    X = [ones(Tp,1) sgn.*log(prices(:,i).*volumes(:,i))];

I am having a hard time creating 'X' without getting the "Data Must be 1 Dimensional Error. Below is one of my attempts, of many trying to reproduce this section of code:

lam = np.empty([Tp,Np]) * np.nan
for i in range(0,Np):
    y=returns.iloc[:,i]
    sgn = modified_sign(y)
    #X = np.array([[np.ones([Tp,1]),np.multiply(np.multiply(sgn,np.log(prices.iloc[:,i])),volumes.iloc[:,i])]])
    X = np.concatenate([np.ones([Tp,1]),np.column_stack(np.array([sgn*np.log(prices.iloc[:,i])*volumes[:,i]]))],axis=1)

Tp and Np are the length and width of the prices series

crsp['PRC'].to_frame().shape = (9455,1)
Tp, Np = crsp['PRC'].to_frame().shape

Tr and Nr are the length and width of the returns series

crsp['RET'].to_frame().shape = (9455,1)
Tr, Nr = crsp['RET'].to_frame().shape

Tv and Nv are the length and width of the volume series

crsp['VOL'].to_frame().shape = (9455,1)
Tv, Nv = crsp['VOL'].to_frame().shape

The ones array:

np.ones([Tp,1])

would be (9455,1)

Sample Volume Data:

    DATE    VOLAVG
1979-12-04  8880.9912591051
1979-12-05  8867.545284586622
1979-12-06  8872.264687564875
1979-12-07  8876.922134551494
1979-12-10  8688.765365448506
1979-12-11  8695.279567657451
1979-12-12  8688.865033222592
1979-12-13  8684.095435684647
1979-12-14  8684.534550736667
1979-12-17  8879.694444444445

Sample Price Data

    DATE    AVGPRC
1979-12-04  25.723484200567693
1979-12-05  25.839463450495863
1979-12-06  26.001899852224145
1979-12-07  25.917628864251874
1979-12-10  26.501898917349788
1979-12-11  26.448652367425804
1979-12-12  26.475906537182407
1979-12-13  26.519610746585908
1979-12-14  26.788873713159944
1979-12-17  26.38583047822484

Sample Return Data

    DATE    RET
1979-12-04  0.008092780873338423
1979-12-05  0.004498557619416754
1979-12-06  0.006266692192175238
1979-12-07  -0.0032462182943131523
1979-12-10  0.022292999386413825
1979-12-11  -0.002011180868938034
1979-12-12  0.001029925340138238
1979-12-13  0.0016493553247958206
1979-12-14  0.010102153877941776
1979-12-17  -0.015159499602784175

What I am ultimately trying to achieve is an (9455,2) array where X.iloc[:,0]=1 and X.iloc[:,2]=log(price)*volume for each row.

I referenced the MatLab to Numpy document online (https://docs.scipy.org/doc/numpy-dev/user/numpy-for-matlab-users.html) and checked out various other StackOverflow posts to no avail.

For context, modified_sign is an external function, prices is a DataFrame slice, as is returns. Np is the width (think df.shape[1]) of the price DataFrame and Tp is df.shape[0]. This is esentially creating a column of 1s and log(price)*volume to be used in a regression for each series of returns where each df is (TxN) where T is dates and N is securities. Any guidance you can provide would be greatly appreciated.

Numpy Array, Data must be 1-dimensional

1 Answers