In [1]:

    

import numpy as np
print("ones", np.ones(5))
print("arange", np.arange(5))
print("linspace", np.linspace(0., 1., 5))
print("random", np.random.uniform(size=3))
print("custom", np.array([2, 3, 5]))


    

    
Out[1]:





ones [ 1.  1.  1.  1.  1.]
arange [0 1 2 3 4]
linspace [ 0.    0.25  0.5   0.75  1.  ]
random [ 0.68361911  0.33585308  0.70733934]
custom [2 3 5]

In [2]:

    

np.array([[1, 2], [3, 4]])


    

    
Out[2]:





array([[1, 2],
       [3, 4]])

In [3]:

    

np.ones(5, dtype=np.int64)


    

    
Out[3]:





array([1, 1, 1, 1, 1])

In [4]:

    

np.arange(5).astype(np.float64)


    

    
Out[4]:





array([ 0.,  1.,  2.,  3.,  4.])

In [5]:

    

import pandas as pd


    

In [6]:

    

data = pd.read_csv('../chapter2/data/nyc_data.csv')


    

In [7]:

    

pickup = data[['pickup_longitude', 'pickup_latitude']].values
pickup


    

    
Out[7]:





array([[-73.955925,  40.781887],
       [-74.005501,  40.745735],
       ...,
       [-73.978477,  40.772945],
       [-73.987206,  40.750568]])

In [8]:

    

pickup.shape


    

    
Out[8]:





(846945, 2)