In [16]:

    

%%bash
conda install pandas_datareader pytables


    

    




Fetching package metadata .........
Solving package specifications: ..........

Package plan for installation in environment /opt/conda:

The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    llvmlite-0.11.0            |           py35_0         7.0 MB
    numpy-1.11.1               |           py35_0         6.1 MB
    h5py-2.6.0                 |      np111py35_1         2.6 MB
    numba-0.26.0               |      np111py35_0         2.1 MB
    numexpr-2.6.0              |      np111py35_0         357 KB
    scipy-0.17.1               |      np111py35_1        29.6 MB
    pandas-0.18.1              |      np111py35_0        14.1 MB
    pytables-3.2.2             |      np111py35_4         3.6 MB
    scikit-learn-0.17.1        |      np111py35_2         8.7 MB
    statsmodels-0.6.1          |      np111py35_1         5.2 MB
    matplotlib-1.5.1           |      np111py35_0         8.4 MB
    scikit-image-0.12.3        |      np111py35_1        26.6 MB
    ------------------------------------------------------------
                                           Total:       114.2 MB

The following NEW packages will be INSTALLED:

    pytables:     3.2.2-np111py35_4                             

The following packages will be UPDATED:

    h5py:         2.6.0-np110py35_1                              --> 2.6.0-np111py35_1 
    llvmlite:     0.8.0-py35_0                                   --> 0.11.0-py35_0     
    matplotlib:   1.5.1-np110py35_0                              --> 1.5.1-np111py35_0 
    numba:        0.23.1-np110py35_0                             --> 0.26.0-np111py35_0
    numexpr:      2.5.2-np110py35_1                              --> 2.6.0-np111py35_0 
    numpy:        1.10.4-py35_blas_openblas_201      conda-forge [blas_openblas] --> 1.11.1-py35_0     
    scikit-image: 0.11.3-np110py35_0                             --> 0.12.3-np111py35_1
    statsmodels:  0.6.1-np110py35_0                  conda-forge --> 0.6.1-np111py35_1 

The following packages will be SUPERCEDED by a higher-priority channel:

    pandas:       0.18.1-np110py35_0                 conda-forge --> 0.18.1-np111py35_0
    scikit-learn: 0.17.1-np110py35_blas_openblas_200 conda-forge [blas_openblas] --> 0.17.1-np111py35_2
    scipy:        0.17.1-np110py35_blas_openblas_200 conda-forge [blas_openblas] --> 0.17.1-np111py35_1

Proceed ([y]/n)? 
Fetching packages ...
llvmlite-0.11. 100% |###############################| Time: 0:00:03   1.98 MB/s
numpy-1.11.1-p 100% |###############################| Time: 0:00:03   1.72 MB/s
h5py-2.6.0-np1 100% |###############################| Time: 0:00:02   1.25 MB/s
numba-0.26.0-n 100% |###############################| Time: 0:00:02   1.05 MB/s
numexpr-2.6.0- 100% |###############################| Time: 0:00:00 412.88 kB/s
scipy-0.17.1-n 100% |###############################| Time: 0:00:10   2.99 MB/s
pandas-0.18.1- 100% |###############################| Time: 0:00:05   2.59 MB/s
pytables-3.2.2 100% |###############################| Time: 0:00:02   1.42 MB/s
scikit-learn-0 100% |###############################| Time: 0:00:04   2.25 MB/s
statsmodels-0. 100% |###############################| Time: 0:00:03   1.75 MB/s
matplotlib-1.5 100% |###############################| Time: 0:00:04   1.89 MB/s
scikit-image-0 100% |###############################| Time: 0:00:09   3.00 MB/s
Extracting packages ...
[      COMPLETE      ]|##################################################| 100%
Unlinking packages ...
[      COMPLETE      ]|##################################################| 100%
Linking packages ...
[      COMPLETE      ]|##################################################| 100%

In [21]:

    

%matplotlib inline

import matplotlib
matplotlib.rcParams['figure.figsize'] = (19, 8)


    

In [25]:

    

from lmk.ticker import Ticker

ticker = Ticker("000001.SS")
# The Grand Stock Market Bubble
ticker.retrieve_history("2015-02-01", "2015-09-30")
ticker.visualize("V,C,CL,LMK,WM,PV")