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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 S&P500 daily stock value get and watch
what's S&P500?
Step1:  dim-1
Step2:  dim-2
Step3:  dim-3
Step4:  preprocessing
notation
$t$
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Python Code:
panel = get_data.symbols2daily_values(kinds='sandp500')
panel
Explanation: S&P500 daily stock value get and watch
what's S&P500?: http://www.investopedia.com/terms/s/sp500.asp
End of explanation
panel.items
Explanation: dim-1: key(item axis)
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panel.major_axis
Explanation: dim-2: date index(monday-friday during 2010~2016)
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panel.minor_axis
Explanation: dim-3: enterprise lists (S&P500 symbols)
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adj_value = preprocess.filter_key_nan(panel, key='Adj Close')
pd.DataFrame(utility.np1(adj_value), columns=['all change rate stats']).describe()
Explanation: preprocessing
notation
$t$: time index
$i$: enterprise symbols index
$x_{t,i}$: $i$-th enterprise adj close (conitinuation) value at time $t$ 
to note change rate,
drop enterprise includes missing value
change rate: $c_{t,i} \leftarrow \log x_{t,i} - \log x_{t-1,i}$ 
all $c_{t,i}$ stats
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