Analyzing Data with Pandas - Time Series

wavedatalab.github.io

% matplotlib inline

import matplotlib.pyplot as plt
import datetime
import pandas as pd

Read the data

yhoo = DataReader("yhoo", "yahoo", datetime.datetime(2007, 1, 1), 
    datetime.datetime(2012,1,1))

Plot stock price and volume

top = plt.subplot2grid((4,4), (0, 0), rowspan=3, colspan=4)
top.plot(yhoo.index, yhoo["Close"])
plt.title('Yahoo Price from 2007 - 2012')

bottom = plt.subplot2grid((4,4), (3,0), rowspan=1, colspan=4)
bottom.bar(yhoo.index, yhoo['Volume'])
plt.title('Yahoo Trading Volume')

plt.gcf().set_size_inches(15,8)

Calculate moving averages

mavg = yhoo['30_MA_Open'] = pd.stats.moments.rolling_mean(yhoo['Open'], 30)
yhoo['30_MA_Open'].tail() 

Date
2011-12-23    15.593000
2011-12-27    15.599667
2011-12-28    15.595000
2011-12-29    15.595667
2011-12-30    15.608333
Name: 30_MA_Open, dtype: float64

Look at selected rows

yhoo[160:165]

	Open	High	Low	Close	Volume	Adj Close	30_MA_Open	150_MA_Open
Date
2007-08-22	23.22	23.52	23.18	23.23	18763700	23.23	24.354000	28.316600
2007-08-23	23.35	23.36	22.95	23.13	15603000	23.13	24.242333	28.286067
2007-08-24	23.03	23.73	23.03	23.59	11191100	23.59	24.114333	28.253933
2007-08-27	23.59	23.76	23.01	23.03	16523800	23.03	24.018000	28.228400
2007-08-28	22.95	23.10	22.50	22.52	18030600	22.52	23.891667	28.192467

Index into a particular date

yhoo.ix['2010-01-04']

Open                 16.940000
High                 17.200000
Low                  16.880000
Close                17.100000
Volume         16587400.000000
Adj Close            17.100000
30_MA_Open           15.806333
150_MA_Open          15.917600
Name: 2010-01-04 00:00:00, dtype: float64

Look at volume for the time period

yhoo.Volume.plot()

<matplotlib.axes._subplots.AxesSubplot at 0x7faf381d13d0>

More plots

yhoo.plot(subplots = True, figsize = (8, 8));
plt.legend(loc = 'best')
plt.show()

close_px = yhoo['Adj Close']
mavg = pd.rolling_mean(close_px, 30)

Moving average plot

yhoo.Close.plot(label='Yahoo')
mavg.plot(label='mavg')
plt.legend()
plt.gcf().set_size_inches(15,8)

KDE plot

yhoo.Close.plot(kind='kde')

<matplotlib.axes._subplots.AxesSubplot at 0x7faf260320d0>