In [1]:

    

from science import *


    

In [2]:

    

temperature_data=pandas.read_csv('temperatures.txt',sep='\s*')  # cleaned version
sunspot_data=pandas.read_csv('spot_num.txt',sep='\s*')


    

In [7]:

    

x=temperature_data['Year']
y=temperature_data['J-D']/100.0

plot(x,y,'-o')
ylabel('Temperature Anomaly')
xlabel('Year')


    

    
Out[7]:





<matplotlib.text.Text at 0xb16db30>






    

In [12]:

    

x=sunspot_data['YEAR']+(sunspot_data['MON']-1)/12.0
y=sunspot_data['SSN']
plot(x,y,'-o')
xlabel('year')
ylabel('sunspot number')


    

    
Out[12]:





<matplotlib.text.Text at 0xb6d9730>






    

In [18]:

    




    

In [37]:

    

ax1=gca()
x=temperature_data['Year']
y=temperature_data['J-D']/100.0
plot(x,y,'-o')
ylabel('Temperature')

x=sunspot_data['YEAR']+(sunspot_data['MON']-1)/12.0
y=sunspot_data['SSN']
y2=pandas.rolling_mean(y,150)

ax2 = gca().twinx()
plot(x,y2,'r-')
ylabel('Sunspot Number')
ax2.set_ylim([20,120])
ax1.set_xlim([1880,2013])
ax2.set_xlim([1880,2013])


    

    
Out[37]:





(1880, 2013)






    

In [34]:

    

pandas.rolling_mean?


    

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