Relative Strength Index in python pandas

Question

I am new to pandas. What is the best way to calculate the relative strength part in the RSI indicator in pandas? So far I got the following:

from pylab impor         


        

Answer 1

My answer is tested on StockCharts sample data.

[StockChart RSI info][1]http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:relative_strength_index_rsi

def RSI(series, period):
    delta = series.diff().dropna()
    u = delta * 0
    d = u.copy()
    u[delta > 0] = delta[delta > 0]
    d[delta < 0] = -delta[delta < 0]
    u[u.index[period-1]] = np.mean( u[:period] ) #first value is sum of avg gains
    u = u.drop(u.index[:(period-1)])
    d[d.index[period-1]] = np.mean( d[:period] ) #first value is sum of avg losses
    d = d.drop(d.index[:(period-1)])
    rs = pd.stats.moments.ewma(u, com=period-1, adjust=False) / \
         pd.stats.moments.ewma(d, com=period-1, adjust=False)
    return 100 - 100 / (1 + rs)


#sample data from StockCharts
data = pd.Series( [ 44.34, 44.09, 44.15, 43.61,
                    44.33, 44.83, 45.10, 45.42,
                    45.84, 46.08, 45.89, 46.03,
                    45.61, 46.28, 46.28, 46.00,
                    46.03, 46.41, 46.22, 45.64 ] )
print RSI( data, 14 )

#output
14    70.464135
15    66.249619
16    66.480942
17    69.346853
18    66.294713
19    57.915021