In [1]:

    

# Magics first (server issues)
%matplotlib inline 
# Do below if you want interactive matplotlib plot ()
# %matplotlib notebook 

# https://ipython.org/ipython-doc/dev/config/extensions/autoreload.html
%load_ext autoreload
%autoreload 2

# %install_ext http://raw.github.com/jrjohansson/version_information/master/version_information.py
%load_ext version_information
%version_information numpy, scipy, matplotlib, pandas


    

    
Out[1]:




Software
Version
Python
2.7.10 64bit [GCC 4.2.1 (Apple Inc. build 5577)]
IPython
3.2.1
OS
Darwin 14.4.0 x86_64 i386 64bit
numpy
1.9.2
scipy
0.15.1
matplotlib
1.4.3
pandas
0.16.2
Fri Jul 24 10:26:20 2015 PDT

In [2]:

    

# Standard library
import os
import sys
sys.path.append("../src/")

# Third party imports
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns

# Local imports
from simpleexample import example_func


    

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# Customizations
sns.set() # matplotlib defaults

# Any tweaks that normally go in .matplotlibrc, etc., should explicitly go here
plt.rcParams['figure.figsize'] = (12, 12)
%config InlineBackend.figure_format='retina'


    

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# Find the notebook the saved figures came from
fig_prefix = "../figures/2015-07-24-jw-"


    

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from IPython.display import FileLink
FileLink("../deliver/coal_data_cleanup.ipynb")


    

    
Out[4]:




../deliver/coal_data_cleanup.ipynb

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dframe = pd.read_csv("../data/coal_prod_cleaned.csv")


    

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plt.scatter(dframe['Year'], dframe['Production_short_tons'])


    

    
Out[6]:





<matplotlib.collections.PathCollection at 0x102db5150>






    

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df2 = dframe.groupby('Mine_State').sum()


    

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df2 = df2[df2.index != 'Wyoming']


    

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sns.jointplot('Labor_Hours', 'Production_short_tons', data=df2, kind="reg", ) 
plt.xlabel("Labor Hours Worked")
plt.ylabel("Total Amount Produced") 
plt.tight_layout()
plt.savefig(fig_prefix + "production-vs-hours-worked.png")


    

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%load_ext autoreload
%autoreload 2


    

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import sys
sys.path.append("../src/")


    

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from simpleexample import example_func
example_func()


    

    
Out[26]:





'This works.'

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example_func()


    

    
Out[27]:





'This works, seriously you can update this.'

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