In [48]:

    

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
%matplotlib inline


    

In [51]:

    

defense_data = pd.read_csv('defense_scouting.csv')


    

In [52]:

    

defense_data


    

    
Out[52]:






  

    

      

      
Team Number
      
Draw Bridge
      
Portcullis
      
Cheval de Frise
      
Rough Terrain
      
Rock Wall
      
Moat
      
Ramparts
      
Low Bar
      
Sally Port
    
  
  

    

      
0
      
2228
      
1
      
0
      
2
      
2
      
2
      
2
      
1
      
2
      
1
    
    

      
1
      
1112
      
2
      
0
      
2
      
2
      
2
      
2
      
1
      
2
      
0
    
    

      
2
      
3455
      
0
      
1
      
2
      
2
      
1
      
2
      
2
      
2
      
0
    
    

      
3
      
2321
      
0
      
1
      
1
      
2
      
1
      
2
      
2
      
2
      
0
    
    

      
4
      
1234
      
0
      
1
      
2
      
2
      
2
      
2
      
2
      
2
      
2
    
    

      
5
      
1123
      
2
      
2
      
1
      
2
      
1
      
2
      
1
      
2
      
1
    
    

      
6
      
1235
      
1
      
1
      
2
      
2
      
2
      
2
      
2
      
2
      
0
    
    

      
7
      
5678
      
1
      
0
      
1
      
1
      
0
      
1
      
1
      
2
      
0
    
  

In [55]:

    

arrayed_data = np.array(defense_data)
arrayed_data


    

    
Out[55]:





array([[2228,    1,    0,    2,    2,    2,    2,    1,    2,    1],
       [1112,    2,    0,    2,    2,    2,    2,    1,    2,    0],
       [3455,    0,    1,    2,    2,    1,    2,    2,    2,    0],
       [2321,    0,    1,    1,    2,    1,    2,    2,    2,    0],
       [1234,    0,    1,    2,    2,    2,    2,    2,    2,    2],
       [1123,    2,    2,    1,    2,    1,    2,    1,    2,    1],
       [1235,    1,    1,    2,    2,    2,    2,    2,    2,    0],
       [5678,    1,    0,    1,    1,    0,    1,    1,    2,    0]])

In [57]:

    

len(arrayed_data)


    

    
Out[57]:





8

In [60]:

    




    

    




  File "<ipython-input-60-22736acfd0b3>", line 1
    i for i in (20, 3, 4, 6, 7)
        ^
SyntaxError: invalid syntax

In [56]:

    

data = arrayed_data

# data = [[  66386,  174296,   75131,  577908,   32015],
#         [  58230,  381139,   78045,   99308,  160454],
#         [  89135,   80552,  152558,  497981,  603535],
#         [  78415,   81858,  150656,  193263,   69638],
#         [ 139361,  331509,  343164,  781380,   52269]]

columns = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')
rows = ['%d year' % x for x in (100, 50, 20, 10, 5)]

values = np.arange(0, 2500, 500)
value_increment = 1000

# Get some pastel shades for the colors
colors = plt.cm.BuPu(np.linspace(0, 0.5, len(rows)))
n_rows = len(data)

index = np.arange(len(columns)) + 0.3
bar_width = 0.4

# Initialize the vertical-offset for the stacked bar chart.
y_offset = np.array([0.0] * len(columns))

# Plot bars and create text labels for the table
cell_text = []
for row in range(n_rows):
    plt.bar(index, data[row], bar_width, bottom=y_offset, color=colors[row])
    y_offset = y_offset + data[row]
    cell_text.append(['%1.1f' % (x/1000.0) for x in y_offset])
# Reverse colors and text labels to display the last value at the top.
colors = colors[::-1]
cell_text.reverse()

# Add a table at the bottom of the axes
the_table = plt.table(cellText=cell_text,
                      rowLabels=rows,
                      rowColours=colors,
                      colLabels=columns,
                      loc='bottom')

# Adjust layout to make room for the table:
plt.subplots_adjust(left=0.2, bottom=0.2)

plt.ylabel("Loss in ${0}'s".format(value_increment))
plt.yticks(values * value_increment, ['%d' % val for val in values])
plt.xticks([])
plt.title('Loss by Disaster')

plt.show()


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-56-92a638eefaf6> in <module>()
     26 cell_text = []
     27 for row in range(n_rows):
---> 28     plt.bar(index, data[row], bar_width, bottom=y_offset, color=colors[row])
     29     y_offset = y_offset + data[row]
     30     cell_text.append(['%1.1f' % (x/1000.0) for x in y_offset])

/Users/dinbecevic/anaconda/lib/python2.7/site-packages/matplotlib/pyplot.pyc in bar(left, height, width, bottom, hold, data, **kwargs)
   2641     try:
   2642         ret = ax.bar(left, height, width=width, bottom=bottom, data=data,
-> 2643                      **kwargs)
   2644     finally:
   2645         ax.hold(washold)

/Users/dinbecevic/anaconda/lib/python2.7/site-packages/matplotlib/__init__.pyc in inner(ax, *args, **kwargs)
   1809                     warnings.warn(msg % (label_namer, func.__name__),
   1810                                   RuntimeWarning, stacklevel=2)
-> 1811             return func(ax, *args, **kwargs)
   1812         pre_doc = inner.__doc__
   1813         if pre_doc is None:

/Users/dinbecevic/anaconda/lib/python2.7/site-packages/matplotlib/axes/_axes.pyc in bar(self, left, height, width, bottom, **kwargs)
   2081         if len(height) != nbars:
   2082             raise ValueError("incompatible sizes: argument 'height' "
-> 2083                               "must be length %d or scalar" % nbars)
   2084         if len(width) != nbars:
   2085             raise ValueError("incompatible sizes: argument 'width' "

ValueError: incompatible sizes: argument 'height' must be length 5 or scalar