［Python数据分析］新股破板买入，赚钱几率如何？
发布时间：2016-11-03 19:10:42 所属栏目：教程 来源：站长网
导读：副标题#e# 这是本人一直比较好奇的问题，网上没搜到，最近在看python数据分析，正好自己动手做一下试试。作者对于python是零基础，需要从头学起。 在写本文时，作者也没有完成这个小分析目标，边学边做吧。 ＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝
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测试运行如下： 
>>> df=ts.get_hist_data('603737')
>>> df
open high close low volume price_change p_change
date
2016-10-28 82.50 82.70 81.53 81.10 8990.79 -0.57 -0.69
2016-10-27 82.30 82.35 82.19 81.34 6959.08 0.24 0.29
2016-10-26 82.04 84.18 81.99 81.51 11004.83 -0.11 -0.13
2016-10-25 82.68 83.32 82.09 82.03 14014.53 -0.89 -1.07
2016-10-24 78.98 83.79 83.00 78.31 26251.55 3.93 4.97
2016-10-21 79.19 79.34 79.08 77.32 12459.65 -0.17 -0.21
2016-10-20 78.50 79.50 79.25 78.05 10224.54 0.75 0.95
2016-10-19 80.60 80.60 78.49 78.44 17851.50 -1.27 -1.59
2016-10-18 77.72 79.80 79.77 77.72 12765.18 1.76 2.26
2016-10-17 78.60 79.70 78.01 77.80 15855.89 -1.07 -1.35
2016-10-14 79.42 80.10 79.00 78.21 11452.91 -0.14 -0.18
2016-10-13 78.85 79.88 79.15 78.20 11277.68 0.18 0.23
2016-10-12 77.17 79.47 78.95 76.60 18557.77 0.90 1.15
2016-10-11 77.95 79.30 78.07 76.63 21518.05 0.05 0.06
2016-10-10 72.93 79.95 78.03 72.93 25128.50 5.11 7.01
2016-09-30 73.08 73.29 72.90 71.90 7940.73 -0.15 -0.20
2016-09-29 73.18 74.16 73.46 73.08 9711.11 0.05 0.07
2016-09-28 73.25 74.10 73.37 72.30 8694.66 0.10 0.14
2016-09-27 72.02 73.31 73.30 71.88 10588.05 0.78 1.08
2016-09-26 76.24 76.24 72.51 72.30 18983.21 -3.77 -4.94
2016-09-23 78.18 78.18 76.31 76.12 13200.18 -1.59 -2.04
2016-09-22 79.10 79.80 77.90 77.61 15900.57 -0.78 -0.99
2016-09-21 79.10 79.80 78.67 77.80 13804.02 -0.96 -1.21
2016-09-20 81.60 81.60 79.64 78.80 15751.28 -1.07 -1.33
2016-09-19 80.56 81.39 80.71 80.48 8901.68 0.12 0.15
2016-09-14 81.80 82.80 80.57 80.28 23667.66 -3.47 -4.13
2016-09-13 86.20 88.16 83.99 83.62 38293.43 -2.19 -2.54
2016-09-12 82.50 86.22 86.19 81.30 30861.92 1.55 1.83
2016-09-09 83.78 85.96 84.66 83.55 23143.33 0.95 1.14
2016-09-08 82.50 83.87 83.71 82.50 13567.35 0.90 1.09
... ... ... ... ... ... ... ...
2016-07-18 100.00 100.98 97.17 96.66 25811.42 -3.71 -3.68
2016-07-15 100.50 103.20 100.90 99.01 35970.92 1.18 1.18
2016-07-14 98.00 100.84 99.73 97.50 29597.28 0.87 0.88
2016-07-13 99.00 101.66 98.87 96.50 38939.97 -1.65 -1.64
2016-07-12 96.96 101.58 100.51 92.06 54520.75 1.13 1.14
2016-07-11 110.00 110.80 99.38 99.38 63645.73 -11.04 -10.00
2016-07-08 111.51 113.40 110.47 110.00 42732.83 -3.25 -2.86
2016-07-07 111.12 118.50 113.71 111.02 64406.13 0.96 0.85
2016-07-06 114.00 115.60 112.75 110.00 57436.00 -2.93 -2.53
2016-07-05 110.11 117.99 115.63 109.10 96591.87 5.25 4.76
2016-07-04 111.89 112.00 110.46 108.33 56773.07 -1.35 -1.21
2016-07-01 111.00 116.00 111.82 108.50 87725.18 -4.26 -3.67
2016-06-30 111.00 116.08 116.08 106.00 179909.75 10.55 10.00
2016-06-29 105.53 105.53 105.53 105.53 1748.55 9.59 10.00
2016-06-28 95.94 95.94 95.94 95.94 2631.18 8.72 10.00
2016-06-27 87.22 87.22 87.22 87.22 10737.11 7.93 10.00
2016-06-24 79.29 79.29 79.29 79.29 2013.69 7.21 10.00
2016-06-23 72.08 72.08 72.08 72.08 2413.01 6.55 9.99
2016-06-22 65.53 65.53 65.53 65.53 1152.33 5.96 10.01
2016-06-21 59.57 59.57 59.57 59.57 998.79 5.42 10.01
2016-06-20 54.15 54.15 54.15 54.15 1332.01 4.92 9.99
2016-06-17 49.23 49.23 49.23 49.23 1086.13 4.48 10.01
2016-06-16 44.75 44.75 44.75 44.75 257.15 4.07 10.01
2016-06-15 40.68 40.68 40.68 40.68 286.50 3.70 10.01
2016-06-14 36.98 36.98 36.98 36.98 627.34 3.36 9.99
2016-06-13 33.62 33.62 33.62 33.62 346.27 3.06 10.01
2016-06-08 30.56 30.56 30.56 30.56 158.75 2.78 10.01
2016-06-07 27.78 27.78 27.78 27.78 35.00 2.53 10.02
2016-06-06 25.25 25.25 25.25 25.25 22.00 2.30 10.02
2016-06-03 22.95 22.95 22.95 22.95 155.00 7.01 43.98
ma5 ma10 ma20 v_ma5 v_ma10 v_ma20 turnover
date
2016-10-28 82.160 80.540 78.207 13444.16 13637.75 14011.51 3.60
2016-10-27 81.670 80.287 77.946 14137.93 13883.97 14221.98 2.78
2016-10-26 81.082 79.983 77.732 14791.02 14315.83 14669.05 4.40
2016-10-25 80.382 79.679 77.566 16160.35 15071.12 14809.01 5.61
2016-10-24 79.918 79.277 77.443 15910.48 15821.47 14895.85 10.50
2016-10-21 78.920 78.780 77.329 13831.35 15709.17 14028.36 4.98
2016-10-20 78.904 78.162 77.403 13630.00 15257.28 14588.76 4.09
2016-10-19 78.884 77.583 77.640 13840.63 15205.93 15992.20 7.14
2016-10-18 78.976 77.071 78.025 13981.89 14290.25 16642.72 5.11
2016-10-17 78.636 76.424 78.270 15732.46 14072.54 17161.63 6.34
2016-10-14 78.640 75.874 78.555 17586.98 14385.27 17047.20 4.58
2016-10-13 77.420 75.605 78.744 16884.55 14559.99 16960.55 4.51
2016-10-12 76.282 75.480 78.975 16571.23 15022.28 17103.11 7.42
2016-10-11 75.166 75.452 79.172 14598.61 14546.91 16525.29 8.61
2016-10-10 74.212 75.609 79.420 12412.61 13970.23 15914.86 10.05
2016-09-30 73.108 75.877 79.673 11183.55 12347.55 15266.72 3.18
2016-09-29 73.790 76.644 80.274 12235.44 13920.24 15776.66 3.88
2016-09-28 74.678 77.697 80.795 13473.33 16778.47 15717.01 3.48
2016-09-27 75.738 78.979 81.333 14495.21 18995.20 15837.12 4.24
2016-09-26 77.006 80.115 81.848 15527.85 20250.73 16159.17 7.59
2016-09-23 78.646 81.235 82.447 13511.55 19709.14 16344.07 5.28
2016-09-22 79.498 81.883 82.944 15605.04 19361.10 16273.08 6.36
2016-09-21 80.716 82.470 83.386 20083.61 19183.94 16362.07 5.52
2016-09-20 82.220 82.891 83.768 23495.19 18503.67 17271.29 6.30
2016-09-19 83.224 83.231 84.417 24973.60 17859.48 17452.37 3.56
2016-09-14 83.824 83.469 85.042 25906.74 18185.89 18336.10 9.47
2016-09-13 84.268 83.905 85.753 23117.16 17633.07 18567.30 15.32
2016-09-12 84.224 83.894 86.355 18284.26 14655.54 18866.01 12.34
2016-09-09 83.562 83.686 86.659 13512.14 12679.05 19115.24 9.26
2016-09-08 83.238 83.580 86.929 10745.36 12067.61 19107.11 5.43
... ... ... ... ... ... ... ...
2016-07-18 99.436 104.912 97.632 36968.07 50965.29 42787.78 10.32
2016-07-15 99.878 106.241 95.481 44534.93 54061.45 41563.81 14.39
2016-07-14 101.792 107.333 92.898 45887.31 59236.88 39819.57 11.84
2016-07-13 104.588 108.968 90.149 52849.08 74268.13 38352.56 15.58
2016-07-12 107.364 109.634 87.239 56548.29 70548.99 36419.89 21.81
2016-07-11 110.388 109.177 84.063 64962.51 65360.03 33725.22 25.46
2016-07-08 112.604 107.961 80.774 63587.98 60069.17 30560.24 17.09
2016-07-07 112.874 104.843 76.779 72586.45 55997.25 28431.54 25.76
2016-07-06 113.348 100.680 72.483 95687.17 49797.94 25212.98 22.97
2016-07-05 111.904 95.958 68.108 84549.68 44169.57 22342.28 38.64
2016-07-04 107.966 90.352 63.474 65757.55 34610.27 17520.44 22.71
2016-07-01 103.318 84.721 61.001 56550.35 29066.16 15454.51 35.09
2016-06-30 96.812 78.462 58.177 39408.06 20402.25 11439.48 71.96
2016-06-29 88.012 71.329 54.771 3908.71 2437.00 1529.46 0.70
2016-06-28 80.012 64.844 51.599 3789.46 2290.79 1515.77 1.05
2016-06-27 72.738 58.948 48.643 3462.99 2090.41 1441.41 4.29
2016-06-24 66.124 53.588 45.887 1581.97 1051.32 777.43 0.81
2016-06-23 60.112 48.715 43.318 1396.45 865.83 682.33 0.97
2016-06-22 54.646 44.285 40.921 965.28 628.03 538.11 0.46
2016-06-21 49.676 40.257 38.684 792.12 514.99 482.27 0.40
2016-06-20 45.158 36.595 36.595 717.83 430.62 430.62 0.53
2016-06-17 41.052 34.644 34.644 520.68 330.46 330.46 0.43
2016-06-16 37.318 32.821 32.821 335.20 236.00 236.00 0.10
2016-06-15 33.924 31.117 31.117 290.77 232.98 232.98 0.11
2016-06-14 30.838 29.523 29.523 237.87 224.06 224.06 0.25
2016-06-13 28.032 28.032 28.032 143.40 143.40 143.40 0.14
2016-06-08 26.635 26.635 26.635 92.69 92.69 92.69 0.06
2016-06-07 25.327 25.327 25.327 70.67 70.67 70.67 0.01
2016-06-06 24.100 24.100 24.100 88.50 88.50 88.50 0.01
2016-06-03 22.950 22.950 22.950 155.00 155.00 155.00 0.06
[97 rows x 14 columns]
View Code
同样，按照第一步的思路对数据稍加处理： df=df[['date','open','close','p_change']] （编辑：源码门户网） 【声明】本站内容均来自网络，其相关言论仅代表作者个人观点，不代表本站立场。若无意侵犯到您的权利，请及时与联系站长删除相关内容! |
