Output numpy.linspace vs numpy.array

Question

I am creating a bar chart using matplotlib. To populate the bar information I was originally using numpy.linspace to create a range of values. I am now trying to populate the bar information with an array of information taken from a mySQLdb.

My issue is that the numpy.linspace output arrays seems to be different than the numpy.array created from a select query and I don't quite understand what is happening.

Here is my original code:

theta = np.linspace(0.0, 2 * np.pi, 20, endpoint=False) #array of indexes for each bar
radii = max_height*np.random.rand(20)    #array of heights/radii for each bar
width = (8*np.pi) / 20   #width of each bar

ax = plt.subplot(111, polar=True)
bars = ax.bar(theta, radii, width=width, bottom=bottom)  #setting each bar value

I am trying to replace the theta variable from above with this code below:

sql = "SELECT theta FROM table LIMIT 20"
cursor.execute(sql)
thetaArray = cursor.fetchall()
thetaSQL = np.array(thetaArray)

When I attempt to use the thetaSQL array I get the following error:

TypeError: only size-1 arrays can be converted to Python scalars

Printing out both arrays returns two slightly different formats:

thetaSQL:
    [[0.        ]
     [0.00314159]
     [0.00628319]
     [0.00942478]
     [0.0125664 ]
     [0.015708  ]
     [0.0188496 ]
     [0.0219911 ]
     [0.0251327 ]
     [0.0282743 ]]
linspace theta:
    [0.         0.62831853 1.25663706 1.88495559 2.51327412 3.14159265
     3.76991118 4.39822972 5.02654825 5.65486678]

How can I make this work with the sql data?

Answer 1

As mentioned by @hpaulj in comments, your options are:

thetaSQL = np.array(thetaArray).ravel()
thetaSQL = np.array(thetaArray).squeeze()
thetaSQL = np.array(thetaArray).reshape(-1)
thetaSQL = np.array(thetaArray)[:,0]

They all convert the 2-D array into 1-D array.