Plot the Nikkei Stock Average with pandas

What to do

If you're playing with Python's data processing library pandas (http://pandas.pydata.org/),

1. Get Finance information from the Web
2. Plot

I posted it because it was wonderful because it was made only with code.

Code and commentary

import pandas.io.data as web
import matplotlib.pyplot as plt
import datetime

#Specify the range of days to get
start = datetime.datetime(2014, 1, 1)
end = datetime.datetime(2014, 9, 1)

#From Yahoo Finance^N225 (Nikkei Stock Average)To
#I will get it.
f = web.DataReader('^N225', 'yahoo', start, end)

plt.title('Nikkei 255 from 2014.1.1 to 2014.9.1')

# fill_Plot the highest and lowest values of the day with between
plt.fill_between(f.index, f['Low'], f['High'], color="b", alpha=0.2)

#Plot the opening price with plot.
#Since Index is automatically set to Date, the horizontal axis is time.

f['Open'].plot()
print f[:10]
plt.show()

Execution result

The pandas DataFrame object looks like this Data is retained as a table.

                Open      High       Low     Close  Volume  Adj Close
Date                                                                 
2014-01-06  16147.54  16164.01  15864.44  15908.88  192700   15908.88
2014-01-07  15835.41  15935.37  15784.25  15814.37  165900   15814.37
2014-01-08  15943.68  16121.45  15906.57  16121.45  206700   16121.45
2014-01-09  16002.88  16004.56  15838.44  15880.33  217400   15880.33
2014-01-10  15785.15  15922.14  15754.70  15912.06  237500   15912.06
2014-01-13  15912.06  15912.06  15912.06  15912.06       0   15912.06
2014-01-14  15657.20  15661.71  15383.69  15422.40  214500   15422.40
2014-01-15  15649.07  15808.73  15636.57  15808.73  185800   15808.73
2014-01-16  15845.15  15941.08  15710.14  15747.20  214200   15747.20
2014-01-17  15695.46  15783.37  15621.80  15734.46  180100   15734.46

Click here for plot results.

By the way

If you change ^ N225 to ʻAAPL`, you can get Apple's stock price. There doesn't seem to be an access API for the Japanese market yet.