get_stock_data_corr_matrix_simple.py

# Build a correlation (and p-value) matrix
r_array = np.zeros([len(symbols_ser), len(symbols_ser)])
p_array = np.zeros([len(symbols_ser), len(symbols_ser)])
for i in range(len(symbols_ser)):
    for j in range(len(symbols_ser)):
        ser_i = total_ticker_df[total_ticker_df.sym == symbols_ser[i]]['close'].values
        ser_j = total_ticker_df[total_ticker_df.sym == symbols_ser[j]]['close'].values
        r_ij, p_ij = scipy.stats.pearsonr(ser_i, ser_j)
        r_array[i, j] = r_ij
        p_array[i, j] = p_ij