列表元素的数值运算

列表元素的数值运算

import numpy as np
res = pd.read_csv(‘20201026分行业数据.csv’, encoding=’gbk’)
res2 = pd.read_csv(‘20201027分行业数据.csv’, encoding=’gbk’)
x = res[‘行业分类’].tolist()
y1 = res[‘BBD(万元)’].tolist()
y2 = res2[‘BBD(万元)’].tolist()
y=y1+y2
print(y1)
print(y2)
a_array = np.array(y1)
b_array = np.array(y2)
c_array = a_array + b_array
print(c_array.tolist())

运行结果:
[1118.9600000000128, -17216.210000000006, -5159.2000000000035, -26785.40000000001, -118616.92999999998, -5461.98, -12057.099999999995, -6327.869999999999, -643250.88, 5589.8899999999985, -108858.05000000008, 2903.360000000002, -4977.080000000002, -34197.349999999984, -56030.56, -21734.619999999995, -1477.3700000000006, -10713.5, -18355.5, -30560.74, 101643.78999999998, -16761.82, -30654.300000000007, -364.53, -87094.13000000005, -71550.57000000004, -3509.4999999999995, -8930.090000000002, -28272.51000000001, -17399.61, -17577.399999999994, 96253.65, -39842.37, -35697.43, -43646.960000000014, -9471.729999999998, -13901.45, -27855.83, -1593.7800000000016, -2074.01, -2483.17, 1653.5500000000006, -186920.6, -22650.66, -10636.48, -26235.59, -6829.130000000001, -36470.29, -16514.4, -3739.049999999999, -4492.389999999996, -243525.35, 83555.81000000001, -68897.28000000004, -27666.99, -253440.71, 7464.639999999994, -7942.83, -252804.52, -91872.79, -387.5600000000002]
[-38000.35000000002, -6438.299999999997, -5998.8600000000015, -51979.13000000002, -42301.08, -8586.41, -9645.46, -7698.0099999999975, -137208.88, 3446.1700000000005, -39694.97000000005, 5897.35, 1433.62, 25779.57999999999, 57376.41000000005, -30385.419999999995, -501.9900000000005, -2634.86, -4227.200000000002, -10248.26, 6914.540000000003, -24620.38, -34615.640000000014, -205.65000000000003, -68036.08999999997, -69753.89999999997, -2837.2300000000014, -4047.27, 900.7900000000003, -6322.019999999998, 23300.09999999999, -61449.51999999998, -26483.15, 8396.5, -106762.43999999996, -14346.729999999998, -11530.890000000007, -18113.82, -34241.630000000005, 2261.57, -3164.81, -9737.209999999995, -119037.80999999994, -120269.82, 420.35999999999984, -5009.710000000001, -12864.41, 185.14999999999938, 25015.57, 2320.5400000000022, 14467.82, -137351.00999999983, -237081.04, -72052.19000000003, -33470.0, -63962.62, 17599.449999999968, -2920.9300000000007, -52645.01000000001, -45289.70000000001, -2723.9299999999994]
[-36881.39000000001, -23654.510000000002, -11158.060000000005, -78764.53000000003, -160918.00999999998, -14048.39, -21702.559999999994, -14025.879999999997, -780459.76, 9036.06, -148553.02000000014, 8800.710000000003, -3543.460000000002, -8417.769999999993, 1345.8500000000495, -52120.03999999999, -1979.360000000001, -13348.36, -22582.7, -40809.0, 108558.32999999999, -41382.2, -65269.94000000002, -570.1800000000001, -155130.22000000003, -141304.47, -6346.730000000001, -12977.360000000002, -27371.72000000001, -23721.629999999997, 5722.699999999997, 34804.13000000001, -66325.52, -27300.93, -150409.39999999997, -23818.459999999995, -25432.340000000007, -45969.65, -35835.41, 187.55999999999995, -5647.98, -8083.659999999994, -305958.4099999999, -142920.48, -10216.119999999999, -31245.300000000003, -19693.54, -36285.14, 8501.169999999998, -1418.5099999999966, 9975.430000000004, -380876.35999999987, -153525.22999999998, -140949.4700000001, -61136.990000000005, -317403.33, 25064.08999999996, -10863.76, -305449.53, -137162.49, -3111.49]