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Journalistically, it is pretty irresponsible to plot these data in the way 538 did. For the sake of this exercise pretending to be unaware of it



In [3]:

    
import pandas as pd
import statsmodels.formula.api as smf
import matplotlib.pyplot as plt
%matplotlib inline



In [41]:

    
df = pd.read_csv('fox_news_data.csv')
df









    Out[41]:






  
    
      
      Unnamed: 0
      approve_obama
      favor_deal
      confident_in_admin_somewhat
      confident_in_admin_very
      confident_admin_total
    
  
  
    
      0
      Democrats
      78
      60
      49
      29
      78
    
    
      1
      Republicans
      10
      34
      13
      4
      17
    
    
      2
      Independent
      37
      44
      29
      15
      44
    
    
      3
      Men
      41
      46
      28
      17
      45
    
    
      4
      Women
      47
      47
      35
      17
      52
    
    
      5
      White
      35
      45
      29
      11
      40
    
    
      6
      Black
      85
      54
      46
      37
      83
    
    
      7
      college_degree
      47
      50
      35
      20
      55
    
    
      8
      no_degree
      43
      45
      29
      14
      43
    
    
      9
      u_35
      56
      51
      39
      18
      57
    
    
      10
      34_54
      35
      46
      29
      13
      42
    
    
      11
      a55
      55
      45
      29
      19
      48
    
    
      12
      a65
      43
      41
      26
      18
      44
    
    
      13
      u55k_income
      48
      47
      34
      18
      52
    
    
      14
      a55k_income
      42
      48
      31
      16
      47
    
    
      15
      Lib
      69
      61
      48
      24
      72
    
    
      16
      Con
      24
      35
      19
      10
      29
    
    
      17
      Tea
      15
      35
      11
      6
      17



In [42]:

    
lm = smf.ols(formula="favor_deal~approve_obama",data=df).fit()
lm.params









    Out[42]:





Intercept        30.690072
approve_obama     0.347628
dtype: float64



In [43]:

    
intercept, slope = lm.params



In [44]:

    
fig, ax = plt.subplots(figsize=(7,7))
plt.style.use('fivethirtyeight')

ax = df.plot(ax = ax, kind='scatter', x="approve_obama", y="favor_deal")
plt.plot(df['approve_obama'],slope*df['approve_obama']+intercept, color="red", linewidth=2)

ax.set_xlim(0,85)
ax.set_ylim(0,85)

ax.set_ylabel("Favor Iran deal")
ax.set_xlabel("Approve of Obama")









    Out[44]:





<matplotlib.text.Text at 0x110d2eeb8>



In [46]:

    
lm2 = smf.ols(formula="confident_admin_total~approve_obama",data=df).fit()
lm2.params









    Out[46]:





Intercept        7.636140
approve_obama    0.898209
dtype: float64



In [47]:

    
intercept2, slope2 = lm2.params



In [48]:

    
fig, ax = plt.subplots(figsize=(7,7))
plt.style.use('fivethirtyeight')

ax = df.plot(ax = ax, kind='scatter', x="approve_obama", y="confident_admin_total")
plt.plot(df['approve_obama'],slope2*df['approve_obama']+intercept2, color="red", linewidth=2)

ax.set_xlim(0,85)
ax.set_ylim(0,85)

ax.set_ylabel("Confident administration will do a good job in negotiations")
ax.set_xlabel("Approve of Obama")









    Out[48]:





<matplotlib.text.Text at 0x110f07860>



In [ ]:

	Unnamed: 0	approve_obama	favor_deal	confident_in_admin_somewhat	confident_in_admin_very	confident_admin_total
0	Democrats	78	60	49	29	78
1	Republicans	10	34	13	4	17
2	Independent	37	44	29	15	44
3	Men	41	46	28	17	45
4	Women	47	47	35	17	52
5	White	35	45	29	11	40
6	Black	85	54	46	37	83
7	college_degree	47	50	35	20	55
8	no_degree	43	45	29	14	43
9	u_35	56	51	39	18	57
10	34_54	35	46	29	13	42
11	a55	55	45	29	19	48
12	a65	43	41	26	18	44
13	u55k_income	48	47	34	18	52
14	a55k_income	42	48	31	16	47
15	Lib	69	61	48	24	72
16	Con	24	35	19	10	29
17	Tea	15	35	11	6	17