In [1]:

    

import pandas as pd
from bs4 import BeautifulSoup
import requests
import matplotlib.pyplot as plt
import seaborn
import re
%matplotlib inline


    

In [2]:

    

opensecrets_lobbying_url = "http://www.opensecrets.org/lobby/"


    

In [3]:

    

r = requests.get(opensecrets_lobbying_url)


    

In [4]:

    

r.status_code


    

    
Out[4]:





200

In [5]:

    

soup = BeautifulSoup(r.text, 'html.parser')


    

In [6]:

    

lobbyingSummaryTable = soup.find("table", { "class": "lobSumTableIn"})


    

In [7]:

    

year_tds = lobbyingSummaryTable.findAll("td", {"align": "center"})
years = [td.string for td in year_tds]


    

In [8]:

    

amount_imgs = lobbyingSummaryTable.findAll("img")
amounts_str = [amount_img['alt'] for amount_img in amount_imgs]
amounts = [re.sub("[^\d\.]", "", amount) for amount in amounts_str]


    

In [9]:

    

lobbyingSummary = pd.DataFrame(index = years)


    

In [10]:

    

lobbyingSummary.insert(loc=0,
                       column="Lobbying Total", 
                       value=pd.to_numeric(amounts))


    

In [11]:

    

lobbyingSummary.plot()


    

    
Out[11]:





<matplotlib.axes._subplots.AxesSubplot at 0x1173d2400>






    

In [12]:

    

fig, ax = plt.subplots()
plt.xlim(1998, 2015)
plt.ylim(0, 4500000000)

#ax.ticklabel_format(useOffset=False)
plt.axvspan(1998, 2009, facecolor="b", alpha=0.1) # bill
plt.axvspan(2001, 2009, facecolor="r", alpha=0.1) # w
plt.axvspan(2009, 2015, facecolor="b", alpha=0.1) # obama
plt.plot(lobbyingSummary.index.values, lobbyingSummary['Lobbying Total'])
plt.figtext(0.135, 0.24, 'Clinton')
plt.figtext(0.42, 0.24, 'Bush')
plt.figtext(0.77, 0.24, 'Obama')
plt.figtext(0.6, 0.84, "Lobbying Spending, yearly")

fig.canvas.draw()
labels = [item.get_text() for item in ax.get_yticklabels()]
labels[-1] = labels[-1] + " billion usd"
labels[0] = ""

ax.set_yticklabels(labels)

plt.show()


    

In [13]:

    

lobbyingSummary["Change"] = lobbyingSummary.pct_change()
lobbyingSummary = lobbyingSummary.fillna(0)


    

In [14]:

    

fig, ax = plt.subplots()
plt.xlim(1998, 2015)
plt.ylim(-30, 30)

#ax.ticklabel_format(useOffset=False)
plt.axvspan(1998, 2009, facecolor="b", alpha=0.1) # bill
plt.axvspan(2001, 2009, facecolor="r", alpha=0.1) # w
plt.axvspan(2009, 2015, facecolor="b", alpha=0.1) # obama
plt.plot(lobbyingSummary.index.values, [x * 100 for x in lobbyingSummary['Change']])
plt.figtext(0.135, 0.24, 'Clinton')
plt.figtext(0.42, 0.24, 'Bush')
plt.figtext(0.77, 0.24, 'Obama')
plt.figtext(0.3, 0.84, "Lobbying Spending, growth over previous year")

fig.canvas.draw()
labels = [item.get_text() + "%" for item in ax.get_yticklabels()]
ax.set_yticklabels(labels)

# draw diagonal line from (70, 90) to (90, 200)
plt.axhline(color="k")

plt.show()


    

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