Intermezzo: A Data Analysis Session

# -*- coding: utf-8 -*-
"""
Created on Wed Nov 05 15:18:17 2014

@author: dell
"""

import pandas as pd
import numpy as np
import datetime
import matplotlib.pyplot as plt
import matplotlib.dates as mdates

if __name__ == ‘__main__‘:
    df = pd.read_table(‘carbon.dioxide.txt‘, header = None)
    data = np.array(list(df[0].values))
    
    fig = plt.figure()
    ax = fig.add_subplot(331)
    ax.plot(data)
    
    x = np.linspace(1, len(data), len(data))
    ax1 = fig.add_subplot(332)
    ax1.plot(data-315)
    ax1.plot(((x/350)**2)*35,‘--‘)
    
    ax3 = fig.add_subplot(333)
    ax3.plot(data-315)
    ax3.plot(((x/350)**1.35)*35, ‘--‘)
    
    ax4 = fig.add_subplot(334)
    myres = data-315-((x/350)**1.35)*35
    ax4.plot(myres)

    ax1 = fig.add_subplot(335)
    from scipy.interpolate import UnivariateSpline
    #xs = np.linspace(1, len(data), len(data)*100)
    xs = np.linspace(1, len(data), 1000)
    s = UnivariateSpline(x, myres)
    ys = s(xs)
    ax1.plot(xs, ys)
    ax1.plot(myres)
    
    ax2 = fig.add_subplot(336)
    ax2.plot(myres)
    ax2.plot(3*np.sin(2*np.pi*x/12))
    
    ax3 = fig.add_subplot(337)
    myres1 = myres - 3*np.sin(2*np.pi*x/12) 
    #myres2 = data - 315-35*(x/350)**1.35 - 3*np.sin(np.pi*2*x/12)
    s1 = UnivariateSpline(x, myres1, s = 850)
    ys1 = s1(xs)
    ax3.plot(xs, ys1)
    ax3.plot(myres1)
    ax3.axhline(y = 1, ls = ‘--‘)
    ax3.axhline(y = -1, ls = ‘:‘)
    
    ax8 = fig.add_subplot(338)
    myfun = 315 + (x/350)**1.35*35 + 3*np.sin(2*np.pi*x/12) + 0.75*np.sin(2*np.pi*x/6) + 0.1
    ax8.plot(myfun, ls=‘:‘)
    ax8.plot(data)
    
    ax9 = fig.add_subplot(339)
    x = np.linspace(1, 800, 800)
    myfun = 315 + (x/350)**1.35*35 + 3*np.sin(2*np.pi*x/12) + 0.75*np.sin(2*np.pi*x/6) + 0.1
    ax9.plot(myfun, ls=‘:‘)
    ax9.plot(data)
    ax9.set_xlim(1, 800)
    
    plt.show()