<jupyter_start><jupyter_text>Here we describe Python Functions:>  . 1) np.arange() >  . 2) np.linspace() >  . 3) np.reshape() >  . 4) np.ravel() >  . 5) np.flatten() >  . 6) np.transpose()<jupyter_code>import numpy as np<jupyter_output><empty_output><jupyter_text>arrange()<jupyter_code># np.arrange(start,end,steps)

arr_1d=np.arange(1,13)

print(arr_1d)
odd_arr=np.arange(1,13,2)
print(odd_arr)<jupyter_output>[ 1  3  5  7  9 11]<jupyter_text>linespace<jupyter_code>np.linspace(1,5,4)<jupyter_output><empty_output><jupyter_text>reshape()  use to change dimenstion of array<jupyter_code>arr_2d=arr_1d.reshape(2,6) # 2 rows and 6 columns
print(arr_2d)
# one to 3d arrayu

arr_3d=arr_1d.reshape(2,3,2)
arr_3d
ar=np.arange(1,13).reshape(2,6)
ar
# ravel convert 3rd dimenstion array to one  dimenstion array 
ar.ravel()<jupyter_output><empty_output><jupyter_text>flatten same<jupyter_code>ar.flatten()<jupyter_output><empty_output><jupyter_text>transpose()<jupyter_code>#  convert row to columns
ar.transpose()
ar.T<jupyter_output><empty_output>
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