In [1]:

    

import pandas as pd


    

In [2]:

    

df = pd.read_csv('data/bouldercreek_09_2013.txt', skiprows=27, header=None, delim_whitespace=True, usecols=[2, 3, 5])
df.columns = ['date', 'time', 'gage_height']
df.head()


    

    
Out[2]:







  

    

      

      
date
      
time
      
gage_height
    
  
  

    

      
0
      
2013-09-01
      
00:00
      
57
    
    

      
1
      
2013-09-01
      
00:15
      
57
    
    

      
2
      
2013-09-01
      
00:30
      
57
    
    

      
3
      
2013-09-01
      
00:45
      
57
    
    

      
4
      
2013-09-01
      
01:00
      
57
    
  

In [3]:

    

import matplotlib.pyplot as plt
%matplotlib inline


    

In [4]:

    

list_numbers = [1.5, 4, 2.2, 5.7]
plt.plot(list_numbers)
plt.show()


    

In [5]:

    

plt.plot([6.8, 4.3, 3.2, 8.1], list_numbers)
plt.show()


    

In [6]:

    

plt.plot([6.8, 4.3, 3.2, 8.1], list_numbers, 'ro-.')
plt.axis([0,10,0,6])
plt.show()


    

In [7]:

    

import numpy as np

t = np.arange(0., 10., 0.5)

plt.plot(t, t, 'r--', t, t**2, 'bs-', t, t**3, 'g^:')

plt.xlabel('This is the x axis')
plt.ylabel('This is the y axis')
plt.title('This is the figure title')

plt.show()


    

In [8]:

    

plt.plot(t, t, 'r--', label='linear')
plt.plot(t, t**2, 'bs-', label='square')
plt.plot(t, t**3, 'g^:', label='cubic')

plt.legend(loc='upper left', shadow=True, fontsize='x-large')

plt.xlabel('This is the x axis')
plt.ylabel('This is the y axis')
plt.title('This is the figure title')

plt.show()


    

In [9]:

    

plt.figure(1)
plt.plot(t, t, 'r--', label='linear')

plt.legend(loc='upper left', shadow=True, fontsize='x-large')
plt.title('This is figure 1')

plt.show()

plt.figure(2)
plt.plot(t, t**2, 'bs-', label='square')

plt.legend(loc='upper left', shadow=True, fontsize='x-large')
plt.title('This is figure 2')

plt.show()


    

In [10]:

    

plt.figure(1)

plt.subplot(2,2,1) # two row, two columns, position 1
plt.plot(t, t, 'r--', label='linear')

plt.subplot(2,2,2) # two row, two columns, position 2
plt.plot(t, t**2, 'bs-', label='square')

plt.subplot(2,2,3) # two row, two columns, position 3
plt.plot(t, t**3, 'g^:', label='cubic')

plt.show()


    

In [11]:

    

plt.plot(df['gage_height'])


    

    
Out[11]:





[<matplotlib.lines.Line2D at 0x10c2e17f0>]