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In [1]:

    
import numpy as np
from datascience import *

# These lines set up graphing capabilities.
import matplotlib
%matplotlib inline
import matplotlib.pyplot as plt
plt.style.use('fivethirtyeight')
import warnings
warnings.simplefilter('ignore', FutureWarning)

from ipywidgets import interact, interactive, fixed, interact_manual
import ipywidgets as widgets



In [4]:

    
table1 = Table.read_table("map_data_CRC.csv")
table1









    Out[4]:





    
        
            state  value
        
    
    
        
            1     0.0569087 
        
    
        
            2     -0.14243  
        
    
        
            4     0.0538141 
        
    
        
            5     -0.08365  
        
    
        
            6     0.0671088 
        
    
        
            8     -0.0857514
        
    
        
            9     -0.14042  
        
    
        
            10    0.116071  
        
    
        
            11    0.0597139 
        
    
        
            12    0.0505135 
        
    

... (41 rows omitted)



In [17]:

    
table2 = Table.read_table("num_data_CRC.csv")
table2.where("group", "Seasonally Adjusted").plot("month", "num")



In [ ]:

    
table3 = Table.read_table("vol_data_CRC.csv")
table3.where("group", "Seasonally Adjusted").where("month", np.arange(84, 132)).plot(0, 1)



In [20]:

    
table4 = Table.read_table("yoy_data_all_CRC.csv")
table4









    Out[20]:





    
        
            month  yoy  group
        
    
    
        
            72    0.0532397  Number of Loans
        
    
        
            73    0.176887  Number of Loans
        
    
        
            74    0.0495053  Number of Loans
        
    
        
            75    0.0538333  Number of Loans
        
    
        
            76    0.0965932  Number of Loans
        
    
        
            77    0.0540308  Number of Loans
        
    
        
            78    0.113789  Number of Loans
        
    
        
            79    0.0383785  Number of Loans
        
    
        
            80    0.094669  Number of Loans
        
    
        
            81    0.0418354  Number of Loans
        
    

... (254 rows omitted)



In [ ]:

state	value
1	0.0569087
2	-0.14243
4	0.0538141
5	-0.08365
6	0.0671088
8	-0.0857514
9	-0.14042
10	0.116071
11	0.0597139
12	0.0505135

month	yoy	group
72	0.0532397	Number of Loans
73	0.176887	Number of Loans
74	0.0495053	Number of Loans
75	0.0538333	Number of Loans
76	0.0965932	Number of Loans
77	0.0540308	Number of Loans
78	0.113789	Number of Loans
79	0.0383785	Number of Loans
80	0.094669	Number of Loans
81	0.0418354	Number of Loans