In [1]:

    

import pandas as pd
import matplotlib.pyplot as plt

%matplotlib inline


    

In [2]:

    

df = pd.read_csv("mn-budget-detail-2014.csv")
df = df.sort_values('amount', ascending=False)
df.head()


    

    
Out[2]:






  

    

      

      
category
      
detail
      
amount
    
  
  

    

      
46
      
ADMINISTRATION
      
Capitol Renovation and Restoration Continued
      
126300000
    
    

      
1
      
UNIVERSITY OF MINNESOTA
      
Minneapolis; Tate Laboratory Renovation
      
56700000
    
    

      
78
      
HUMAN SERVICES
      
Minnesota Security Hospital - St. Peter
      
56317000
    
    

      
0
      
UNIVERSITY OF MINNESOTA
      
Higher Education Asset Preservation (HEAPR) 1
      
42500000
    
    

      
5
      
MINNESOTA STATE COLLEGES AND UNIVERSITIES
      
Higher Education Asset Preservation (HEAPR) 2
      
42500000
    
  

In [4]:

    

sizes = df.groupby('category').size()
sizes.plot(kind='barh', figsize=(15,10))


    

    
Out[4]:





<matplotlib.axes._subplots.AxesSubplot at 0x10c8e0090>






    

In [5]:

    

import seaborn as sns
sns.set_style('white')


    

In [6]:

    

sizes.plot(kind='bar', figsize=(15,10))


    

    
Out[6]:





<matplotlib.axes._subplots.AxesSubplot at 0x11024f910>






    

In [10]:

    

sns.set_context('poster')
bar_plot = sns.barplot(x=sizes.index.values, y=sizes.values, palette="BuGn_r", order=sizes.index.values.tolist())
plt.xticks(rotation=90)


    

    
Out[10]:





(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,
        17, 18, 19, 20, 21, 22, 23]), <a list of 24 Text xticklabel objects>)






    

In [11]:

    

from ggplot import *


    

In [12]:

    

# dfs = sizes.to_frame(name='count').reset_index()
# dfs['count'] = dfs['count'].astype(float)
# print(dfs.columns)
# print(dfs.index)
# print(dfs.head())
# print(dfs['category'].tolist())
# print(dfs['count'])

dfs = df.sort_values('amount',ascending=False)[:10]

p = ggplot(dfs, aes(x="category",y="amount")) + \
    geom_bar(stat="bar", labels=dfs["category"].tolist()) +\
    ggtitle("MN Capital Budget - 2014") + \
    xlab("Categories") +  \
    ylab("Coutns") + scale_y_continuous(labels='millions') + \
    theme(axis_text_x=element_text(angle=90))
print p


    

    













    




<ggplot: (286317633)>

In [13]:

    

from bokeh.charts import Bar, show


    

In [14]:

    

bar = Bar(sizes, filename="bar.html", title="MN Capital Budget - 2014", legend=False)
show(bar)


    

In [15]:

    

import pygal
from pygal.style import LightStyle


    

In [16]:

    

bar_chart = pygal.Bar(style=LightStyle, width=800, height=600,
                      legend_at_bottom=True, human_readable=True,
                      title='MN Capital Budget - 2014')


    

In [17]:

    

for index, row in sizes.iteritems():
    bar_chart.add(index, row)


    

In [18]:

    

# bar_chart.render_to_file('budget.svg')
# bar_chart.render_to_png('budget.png')
bar_chart.render_in_browser()


    

    




file:///var/folders/5g/krkdym5x1f7fjkqy18dzlhnc0000gp/T/tmpau9VXc.html

In [19]:

    

import plotly.plotly as py
from plotly.graph_objs import *


    

In [20]:

    

data = Data([
    Bar(
        x=sizes.index,
        y=sizes.values
    )
])


    

In [21]:

    

layout = Layout(
    title='2014 MN Capital Budget',
    font=Font(
        family='Raleway, sans-serif'
    ),
    showlegend=False,
    xaxis=XAxis(
        tickangle=-45
    ),
    bargap=0.05
)

fig = Figure(data=data, layout=layout)
plot_url = py.plot(data,filename='MN Capital Budget - 2014')
py.image.save_as(fig, 'mn-14-budget.png')


    

In [ ]: