In [1]:

    

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline

# Optional for interactive
# %matplotlib notebook (watch video for full details)


    

In [2]:

    

mcdon = pd.read_csv('mcdonalds.csv',
                    index_col = 'Date',
                    parse_dates = True)


    

In [3]:

    

mcdon.head()


    

    
Out[3]:







  

    

      

      
Adj. Close
      
Adj. Volume
    
    

      
Date
      

      

    
  
  

    

      
1970-01-02
      
0.209761
      
2825604.0
    
    

      
1970-01-05
      
0.213316
      
2210449.5
    
    

      
1970-01-06
      
0.214501
      
1951168.5
    
    

      
1970-01-07
      
0.213316
      
2728768.5
    
    

      
1970-01-08
      
0.213316
      
2242404.0
    
  

In [4]:

    

# Not Good!
mcdon.plot()


    

    
Out[4]:





<matplotlib.axes._subplots.AxesSubplot at 0x1911a3667f0>






    

In [5]:

    

mcdon['Adj. Close'].plot()


    

    
Out[5]:





<matplotlib.axes._subplots.AxesSubplot at 0x19119998b70>






    

In [6]:

    

mcdon['Adj. Volume'].plot()


    

    
Out[6]:





<matplotlib.axes._subplots.AxesSubplot at 0x19119cbc5c0>






    

In [7]:

    

mcdon['Adj. Close'].plot(figsize = (12, 8))


    

    
Out[7]:





<matplotlib.axes._subplots.AxesSubplot at 0x19119dd4be0>






    

In [8]:

    

mcdon['Adj. Close'].plot(figsize = (12, 8))
plt.ylabel('Close Price')
plt.xlabel('Overwrite Date Index')
plt.title('Mcdonalds')


    

    
Out[8]:





<matplotlib.text.Text at 0x1911a041d68>






    

In [9]:

    

mcdon['Adj. Close'].plot(figsize = (12,8),
                         title = 'Pandas Title')


    

    
Out[9]:





<matplotlib.axes._subplots.AxesSubplot at 0x1911a136ba8>






    

In [10]:

    

mcdon['Adj. Close'].plot(xlim = ['2007-01-01', '2009-01-01'])


    

    
Out[10]:





<matplotlib.axes._subplots.AxesSubplot at 0x1911b4d6588>






    

In [11]:

    

mcdon['Adj. Close'].plot(xlim = ['2007-01-01','2009-01-01'],
                         ylim = [0,50])


    

    
Out[11]:





<matplotlib.axes._subplots.AxesSubplot at 0x1911b4f05c0>






    

In [12]:

    

mcdon['Adj. Close'].plot(xlim = ['2007-01-01','2007-05-01'],
                         ylim = [0,40],
                         ls = '--',
                         c = 'r')


    

    
Out[12]:





<matplotlib.axes._subplots.AxesSubplot at 0x1911b5d7dd8>






    

In [13]:

    

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


    

In [14]:

    

mcdon['Adj. Close'].plot(xlim = ['2007-01-01','2007-05-01'],
                         ylim = [0,40])


    

    
Out[14]:





<matplotlib.axes._subplots.AxesSubplot at 0x1911b640198>






    

In [15]:

    

idx = mcdon.loc['2007-01-01':'2007-05-01'].index
stock = mcdon.loc['2007-01-01':'2007-05-01']['Adj. Close']


    

In [16]:

    

idx


    

    
Out[16]:





DatetimeIndex(['2007-01-03', '2007-01-04', '2007-01-05', '2007-01-08',
               '2007-01-09', '2007-01-10', '2007-01-11', '2007-01-12',
               '2007-01-16', '2007-01-17', '2007-01-18', '2007-01-19',
               '2007-01-22', '2007-01-23', '2007-01-24', '2007-01-25',
               '2007-01-26', '2007-01-29', '2007-01-30', '2007-01-31',
               '2007-02-01', '2007-02-02', '2007-02-05', '2007-02-06',
               '2007-02-07', '2007-02-08', '2007-02-09', '2007-02-12',
               '2007-02-13', '2007-02-14', '2007-02-15', '2007-02-16',
               '2007-02-20', '2007-02-21', '2007-02-22', '2007-02-23',
               '2007-02-26', '2007-02-27', '2007-02-28', '2007-03-01',
               '2007-03-02', '2007-03-05', '2007-03-06', '2007-03-07',
               '2007-03-08', '2007-03-09', '2007-03-12', '2007-03-13',
               '2007-03-14', '2007-03-15', '2007-03-16', '2007-03-19',
               '2007-03-20', '2007-03-21', '2007-03-22', '2007-03-23',
               '2007-03-26', '2007-03-27', '2007-03-28', '2007-03-29',
               '2007-03-30', '2007-04-02', '2007-04-03', '2007-04-04',
               '2007-04-05', '2007-04-09', '2007-04-10', '2007-04-11',
               '2007-04-12', '2007-04-13', '2007-04-16', '2007-04-17',
               '2007-04-18', '2007-04-19', '2007-04-20', '2007-04-23',
               '2007-04-24', '2007-04-25', '2007-04-26', '2007-04-27',
               '2007-04-30', '2007-05-01'],
              dtype='datetime64[ns]', name='Date', freq=None)

In [17]:

    

stock


    

    
Out[17]:





Date
2007-01-03    31.662754
2007-01-04    31.424580
2007-01-05    31.424580
2007-01-08    31.547276
2007-01-09    31.605015
2007-01-10    31.944233
2007-01-11    32.124668
2007-01-12    31.915364
2007-01-16    32.167973
2007-01-17    32.377277
2007-01-18    32.182407
2007-01-19    32.341190
2007-01-22    32.009190
2007-01-23    32.370060
2007-01-24    31.872059
2007-01-25    31.034840
2007-01-26    30.984318
2007-01-29    31.200840
2007-01-30    31.590580
2007-01-31    32.009190
2007-02-01    32.103016
2007-02-02    32.146320
2007-02-05    32.139103
2007-02-06    32.312321
2007-02-07    32.276234
2007-02-08    32.009190
2007-02-09    32.160755
2007-02-12    32.283451
2007-02-13    32.406147
2007-02-14    32.492756
                ...    
2007-03-20    31.980320
2007-03-21    32.196842
2007-03-22    32.110233
2007-03-23    32.514408
2007-03-26    32.564930
2007-03-27    32.507191
2007-03-28    32.355625
2007-03-29    32.384495
2007-03-30    32.514408
2007-04-02    32.348408
2007-04-03    32.665974
2007-04-04    32.644321
2007-04-05    33.041279
2007-04-09    33.553714
2007-04-10    33.423801
2007-04-11    33.517627
2007-04-12    33.654758
2007-04-13    34.383716
2007-04-16    34.715717
2007-04-17    35.372500
2007-04-18    35.278674
2007-04-19    35.206500
2007-04-20    34.903369
2007-04-23    35.105456
2007-04-24    34.982761
2007-04-25    35.098239
2007-04-26    35.531283
2007-04-27    35.329196
2007-04-30    34.845630
2007-05-01    35.466327
Name: Adj. Close, Length: 82, dtype: float64

In [18]:

    

fig, ax = plt.subplots()
ax.plot_date(idx, stock,'-')
plt.tight_layout()
plt.show()


    

In [19]:

    

fig, ax = plt.subplots()
ax.plot_date(idx, stock,'-')

fig.autofmt_xdate() # Auto fixes the overlap!
plt.tight_layout()
plt.show()


    

In [20]:

    

fig, ax = plt.subplots()
ax.plot_date(idx, stock,'-')
ax.yaxis.grid(True)
ax.xaxis.grid(True)
fig.autofmt_xdate() # Auto fixes the overlap!
plt.tight_layout()
plt.show()


    

In [21]:

    

fig, ax = plt.subplots()
ax.plot_date(idx, stock,'-')

# Grids
ax.yaxis.grid(True)
ax.xaxis.grid(True)

# Major Axis
ax.xaxis.set_major_locator(dates.MonthLocator())
ax.xaxis.set_major_formatter(dates.DateFormatter('%b\n%Y'))

fig.autofmt_xdate() # Auto fixes the overlap!
plt.tight_layout()
plt.show()


    

In [22]:

    

fig, ax = plt.subplots()
ax.plot_date(idx, stock,'-')

# Grids
ax.yaxis.grid(True)
ax.xaxis.grid(True)

# Major Axis
ax.xaxis.set_major_locator(dates.MonthLocator())
ax.xaxis.set_major_formatter(dates.DateFormatter('\n\n\n\n%Y--%B'))

fig.autofmt_xdate() # Auto fixes the overlap!
plt.tight_layout()
plt.show()


    

In [23]:

    

fig, ax = plt.subplots()
ax.plot_date(idx, stock,'-')


# Major Axis
ax.xaxis.set_major_locator(dates.MonthLocator())
ax.xaxis.set_major_formatter(dates.DateFormatter('\n\n%Y--%B'))

# Minor Axis
ax.xaxis.set_minor_locator(dates.WeekdayLocator())
ax.xaxis.set_minor_formatter(dates.DateFormatter('%d'))

# Grids
ax.yaxis.grid(True)
ax.xaxis.grid(True)

fig.autofmt_xdate() # Auto fixes the overlap!
plt.tight_layout()
plt.show()


    

In [24]:

    

fig, ax = plt.subplots(figsize=(10,8))
ax.plot_date(idx, stock,'-')


# Major Axis
ax.xaxis.set_major_locator(dates.WeekdayLocator(byweekday=1))
ax.xaxis.set_major_formatter(dates.DateFormatter('%B-%d-%a'))
# Grids
ax.yaxis.grid(True)
ax.xaxis.grid(True)

fig.autofmt_xdate() # Auto fixes the overlap!

plt.tight_layout()
plt.show()