import panda as pd
df.head()
df.tail()
df.info()
np.log10(df.values)
numpy arrays, matrix

shape = (2,2)
np.empty(shape)
np.ones(shape)
np.zeros(shape)
np.array(some_list), np.asarray(some_list), np.reshape(shape), np.empty_like(some_array)
arr[:,:] #get all values od 2dim arr


np.random.randint(-100, 100, 9)  #9 random int in [-100, 100)
np.random.ranf(size=1)  #random floats in [0.0,1.0)

np.random.sample(size=1)
(b - a) * random_sample() + a

np.matrix(some_list.reshape(shape))
mprod = mtrx1.dot(mtrx2)                #matrix multiplication
mprod_inversed = np.linalg.inv(mprod)   #inverse
mprod.transpose()                       #transpose