Bar Chart - python/matplotlib

[ChrissyWhite]

I have a python script that does a variety of things within ArcMap. Within that script, I output a list (generated from a loop that appends to it) that gives me this:

[[['AB', 2.76]], [['D', 3.95]], [['E', 6.22]], [['F', 7.23]], [['G', 9.51]], [['H', 10.69]], [['I', 11.11]], [['J', 11.65]], [['K', 11.82]], [['L', 12.11]], [['M', 13.37]], [['N', 14.04]], [['O', 15.11]], [['P', 15.44]]]

I need to create a bar chart, using matplotlib from this list. This is what I have done:

xs = np.arange(len(gphList))

data = np.array(gphList)
labels, y1 = data.T
ys = y1.astype(float)
plt.bar(xs, ys, color="black")

There is a bit more, but it fails at the plt.bar line, and I can't figure out why.

My "data" gives me this:

[[['AB' '2.76']]

　

[['D' '3.95']]

　

[['E' '6.22']]

　

[['F' '7.23']]

　

[['G' '9.51']]

　

[['H' '10.69']]

　

[['I' '11.11']]

　

[['J' '11.65']]

　

[['K' '11.82']]

　

[['L' '12.11']]

　

[['M' '13.37']]

　

[['N' '14.04']]

　

[['O' '15.11']]

　

[['P' '15.44']]]

My "xs" gives me:

[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13]

My "ys" gives me:

[[ 2.76 3.95 6.22 7.23 9.51 10.69 11.11 11.65 11.82 12.11 13.37 14.04 15.11 15.44]]

And my "labels" gives me:

[['AB' 'D' 'E' 'F' 'G' 'H' 'I' 'J' 'K' 'L' 'M' 'N' 'O' 'P']]

Which all seem fine to me, but I receive this error:

ValueError: incompatible sizes: argument 'height' must be length 14 or scalar

I am really lost on why it is doing that. The height (ys) is the list of values for the height....why is it complaining? How do I make it happy?

[DanPatterson_Retired · Accepted solution]

Your original construct of the data was incorrect, it had an extra dimension... try the following data and observe the steps to obtain it.

a = np.array([[['AB', 2.76]], [['D', 3.95]], [['E', 6.22]], [['F', 7.23]], [['G', 9.51]], [['H', 10.69]], [['I', 11.11]], [['J', 11.65]], [['K', 11.82]], [['L', 12.11]], [['M', 13.37]], [['N', 14.04]], [['O', 15.11]], [['P', 15.44]]])

a
Out[2]: 
array([[['AB', '2.76']],

       [['D', '3.95']],

       [['E', '6.22']],

       [['F', '7.23']],

       [['G', '9.51']],

       [['H', '10.69']],

       [['I', '11.11']],

       [['J', '11.65']],

       [['K', '11.82']],

       [['L', '12.11']],

       [['M', '13.37']],

       [['N', '14.04']],

       [['O', '15.11']],

       [['P', '15.44']]],
      dtype='<U5')

a0 = a.squeeze()  # ---- get rid of the extra dimension

a0                # ---- much better
Out[4]: 
array([['AB', '2.76'],
       ['D', '3.95'],
       ['E', '6.22'],
       ['F', '7.23'],
       ['G', '9.51'],
       ['H', '10.69'],
       ['I', '11.11'],
       ['J', '11.65'],
       ['K', '11.82'],
       ['L', '12.11'],
       ['M', '13.37'],
       ['N', '14.04'],
       ['O', '15.11'],
       ['P', '15.44']],
      dtype='<U5')

xs = np.arange(len(a0))  # ---- generate the xs

data = np.array(a0)      # ---- not needed, just some renaming
labels, y1 = data.T      # ---- translate the arrays and assign to labels and ys
ys = y1.astype(float)



labels   # ---- check the values
Out[7]: 
array(['AB', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O',
       'P'],
      dtype='<U5')

ys
Out[8]: 
array([  2.76,   3.95,   6.22,   7.23,   9.51,  10.69,  11.11,  11.65,
        11.82,  12.11,  13.37,  14.04,  15.11,  15.44])

xs
Out[9]: array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13])
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Now make your graph

import matplotlib.pyplot as plt

plt.bar(xs, ys, color="black")
Out[15]: <Container object of 14 artists>‍‍‍‍

[ChrissyWhite]

That was perfect, thank you so much!!!