python - Making a faster wavelet transform/Appending data faster -

i taking 1-d wavelet transform of data. how can make faster? have 1.4 million samples , 32 features.

def apply_wavelet_transform(data):     ca,cd=pywt.dwt(data[0,:],'haar')     in range(1,data.shape[0]):         ca_i,__=pywt.dwt(data[i,:],'haar')         ca=np.vstack((ca,ca_i))     return ca 

consider don't care memory usage as speed of execution.

this common mistake. don't want append rows array 1 @ time, because each iteration requires copying entire array. complexity: o(n**2). better keep intermediate results in list , form array @ end. better because lists not require elements contiguous in memory, no copying required.

def apply_wavelet_transform(data):     results_list = []     row in data:         ca, cd = pywt.dwt(row, 'haar')         results_list.append(ca)     result = np.array(results_list)     return result