import jqdata as jq
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
a=get_mtss('002038.XSHE', '2018-01-01', '2018-07-20')
b=get_price('002038.XSHE', '2018-01-01', '2018-07-20',fields='close')
print(a)
print(b)
date sec_code fin_value fin_buy_value fin_refund_value \
0 2018-01-02 002038.XSHE 1559566392 30328094 49738674
1 2018-01-03 002038.XSHE 1559620601 31038894 30984685
2 2018-01-04 002038.XSHE 1585682984 75697116 49634733
3 2018-01-05 002038.XSHE 1578678663 38560939 45565260
4 2018-01-08 002038.XSHE 1592058672 47760445 34380436
5 2018-01-09 002038.XSHE 1601788086 97766494 88037080
6 2018-01-10 002038.XSHE 1589709383 40082697 52161400
7 2018-01-11 002038.XSHE 1583798462 49965199 55876120
8 2018-01-12 002038.XSHE 1566256850 38479590 56021202
9 2018-01-15 002038.XSHE 1556586822 49567895 59237923
10 2018-01-16 002038.XSHE 1546763663 24329493 34152652
11 2018-01-17 002038.XSHE 1528637974 29670602 47796291
12 2018-01-18 002038.XSHE 1527269852 17995137 19363259
13 2018-01-19 002038.XSHE 1525596418 28211725 29885159
14 2018-01-22 002038.XSHE 1527480191 30301773 28418000
15 2018-01-23 002038.XSHE 1523805999 22458398 26132590
16 2018-01-24 002038.XSHE 1543038942 70029417 50796474
17 2018-01-25 002038.XSHE 1544001411 39168696 38206227
18 2018-01-26 002038.XSHE 1530819646 67917098 81098863
19 2018-01-29 002038.XSHE 1521313142 39531731 49038235
20 2018-01-30 002038.XSHE 1523177214 24225125 22361053
21 2018-01-31 002038.XSHE 1554239809 61737543 30674948
22 2018-02-01 002038.XSHE 1556167612 41029888 39102085
23 2018-02-02 002038.XSHE 1542354869 27388484 41201227
24 2018-02-05 002038.XSHE 1538888067 36957677 40424479
25 2018-02-06 002038.XSHE 1522051855 54331798 71168010
26 2018-02-07 002038.XSHE 1505524226 26519539 43047168
27 2018-02-08 002038.XSHE 1503469615 26079872 28134483
28 2018-02-09 002038.XSHE 1502155249 26907937 28222303
29 2018-02-12 002038.XSHE 1495091087 21872521 28936683
.. ... ... ... ... ...
103 2018-06-07 002038.XSHE 1959118043 78331052 59479515
104 2018-06-08 002038.XSHE 1933181121 49491640 75428562
105 2018-06-11 002038.XSHE 1789909108 68247188 211519201
106 2018-06-12 002038.XSHE 1795195018 112791892 107505982
107 2018-06-13 002038.XSHE 1779591983 67246868 82849903
108 2018-06-14 002038.XSHE 1787752654 112632633 104471962
109 2018-06-15 002038.XSHE 1796606761 100476095 91621988
110 2018-06-19 002038.XSHE 1813128510 188831237 172309488
111 2018-06-20 002038.XSHE 1779546420 113531294 147113384
112 2018-06-21 002038.XSHE 1750789845 273199349 301955924
113 2018-06-22 002038.XSHE 1807228675 217587293 161148463
114 2018-06-25 002038.XSHE 1842782436 149608132 114054371
115 2018-06-26 002038.XSHE 1819965324 55153138 77970250
116 2018-06-27 002038.XSHE 1823433227 99475360 96007457
117 2018-06-28 002038.XSHE 1807676837 43973715 59730105
118 2018-06-29 002038.XSHE 1792770306 75944962 90851493
119 2018-07-02 002038.XSHE 1816469856 109364510 85664960
120 2018-07-03 002038.XSHE 1822914432 100982945 94538369
121 2018-07-04 002038.XSHE 1829623546 49268582 42559468
122 2018-07-05 002038.XSHE 1822052743 57252031 64822834
123 2018-07-06 002038.XSHE 1824018730 59371951 57405964
124 2018-07-09 002038.XSHE 1790620668 48294942 81693004
125 2018-07-10 002038.XSHE 1786260094 50179673 54540247
126 2018-07-11 002038.XSHE 1782788439 48383839 51855494
127 2018-07-12 002038.XSHE 1683531236 71932205 171189408
128 2018-07-13 002038.XSHE 1652043245 93921863 125409854
129 2018-07-16 002038.XSHE 1653772534 55282543 53553254
130 2018-07-17 002038.XSHE 1694272734 81465054 40964854
131 2018-07-18 002038.XSHE 1694497464 48220407 47995677
132 2018-07-19 002038.XSHE 1733864102 125636687 86270049
sec_value sec_sell_value sec_refund_value fin_sec_value
0 20500 12000 16100 1560206197
1 20200 3900 4200 1560257911
2 24600 8300 3900 1586468954
3 23600 4000 5000 1579421591
4 5800 2900 20700 1592239168
5 41400 39000 3400 1603115370
6 4200 1800 39000 1589842901
7 6100 2500 600 1583995126
8 3000 0 3100 1566355220
9 4100 1200 100 1556718022
10 12300 9400 1200 1547162306
11 13700 1400 0 1529075689
12 13700 0 0 1527705786
13 13000 1200 1900 1526003968
14 2400 0 10600 1527557351
15 2400 0 0 1523883279
16 2900 600 100 1543135077
17 3700 1400 600 1544123326
18 8300 6000 1400 1531097530
19 5000 2700 6000 1521477842
20 6000 2000 1000 1523376534
21 5000 1000 2000 1554400209
22 13900 8900 0 1556607547
23 6700 0 7200 1542563105
24 15300 11000 2400 1539347832
25 4100 0 11200 1522163580
26 4600 3200 2700 1505651002
27 4300 0 300 1503588897
28 5800 2700 1200 1502311849
29 4800 1200 2200 1495225295
.. ... ... ... ...
103 53560 3000 11400 1961616617
104 54560 11300 10300 1935694700
105 56560 14400 12400 1792469014
106 61960 15600 10200 1798118910
107 61960 12400 12400 1782477460
108 57888 12800 16872 1790372086
109 54407 13619 17100 1799098602
110 48507 17900 23800 1815250691
111 48907 16700 16300 1781756038
112 38107 10400 21200 1752339276
113 54607 31500 15000 1809328314
114 46807 12700 20500 1844495572
115 47007 18900 18700 1821730437
116 44107 24800 27700 1825021520
117 51607 21900 14400 1809540366
118 40379 11272 22500 1794304304
119 47079 16400 9700 1818221666
120 31679 21100 36500 1824073567
121 38679 21500 14500 1831024886
122 54179 30700 15200 1823960927
123 34579 16600 36200 1825258733
124 44879 23800 13500 1792283884
125 37705 16026 23200 1787654048
126 52505 34600 19800 1784686495
127 61105 49400 40800 1685842838
128 108305 55300 8100 1656214071
129 73105 18100 53300 1656595118
130 89805 35400 18700 1697678140
131 92505 32900 30200 1697943275
132 79205 23700 37000 1736650534
[133 rows x 9 columns]
close
2018-01-02 30.87
2018-01-03 31.20
2018-01-04 31.60
2018-01-05 31.13
2018-01-08 30.78
2018-01-09 31.71
2018-01-10 31.44
2018-01-11 31.89
2018-01-12 32.43
2018-01-15 31.65
2018-01-16 32.05
2018-01-17 31.60
2018-01-18 31.47
2018-01-19 31.00
2018-01-22 31.80
2018-01-23 31.85
2018-01-24 32.78
2018-01-25 32.59
2018-01-26 33.11
2018-01-29 32.58
2018-01-30 32.85
2018-01-31 31.73
2018-02-01 31.30
2018-02-02 30.74
2018-02-05 29.72
2018-02-06 26.95
2018-02-07 27.26
2018-02-08 27.43
2018-02-09 26.70
2018-02-12 27.65
... ...
2018-06-08 46.07
2018-06-11 45.26
2018-06-12 47.19
2018-06-13 46.57
2018-06-14 45.25
2018-06-15 45.80
2018-06-19 43.75
2018-06-20 45.18
2018-06-21 40.66
2018-06-22 38.45
2018-06-25 36.60
2018-06-26 37.55
2018-06-27 36.01
2018-06-28 36.11
2018-06-29 37.99
2018-07-02 37.21
2018-07-03 36.59
2018-07-04 36.23
2018-07-05 35.22
2018-07-06 35.86
2018-07-09 37.06
2018-07-10 36.97
2018-07-11 36.15
2018-07-12 37.83
2018-07-13 38.51
2018-07-16 38.61
2018-07-17 37.92
2018-07-18 37.25
2018-07-19 35.18
2018-07-20 35.98
[134 rows x 1 columns]
plt.figure(figsize=[18,5])
a['sec_value'].plot(label='sec_value')
a['sec_sell_value'].plot(label='sec_sell_value')
b.plot()
plt.legend(loc='best')
<matplotlib.legend.Legend at 0x7f25628cab00>
df = get_price(get_industry_stocks('A01'), fields=('close',))['close']
print(df)
plt.figure(figsize=[18,5])
df['000998.XSHE'].plot()
pd.rolling_mean(df['000998.XSHE'],20).plot(label='20 day moving average')
pd.rolling_mean(df['000998.XSHE'],5).plot(label='5 day moving average')
plt.legend(loc='best')
000998.XSHE 002041.XSHE 002772.XSHE 300087.XSHE 300189.XSHE \
2015-01-05 19.34 12.71 NaN 3.96 2.71
2015-01-06 19.73 12.92 NaN 4.08 2.78
2015-01-07 19.57 12.85 NaN 4.04 2.76
2015-01-08 20.11 13.03 NaN 4.13 2.77
2015-01-09 19.75 12.87 NaN 4.02 2.72
2015-01-12 19.22 12.98 NaN 3.91 2.66
2015-01-13 19.59 13.15 NaN 4.04 2.73
2015-01-14 19.21 12.96 NaN 3.98 2.68
2015-01-15 19.37 13.04 NaN 4.05 2.70
2015-01-16 19.77 13.26 NaN 4.17 2.76
2015-01-19 19.21 13.31 NaN 4.12 2.66
2015-01-20 19.61 13.55 NaN 4.26 2.73
2015-01-21 20.03 13.79 NaN 4.38 2.80
2015-01-22 20.62 13.92 NaN 4.41 2.88
2015-01-23 20.21 13.66 NaN 4.33 2.83
2015-01-26 20.31 13.76 NaN 4.35 2.86
2015-01-27 20.76 13.94 NaN 4.61 2.91
2015-01-28 20.30 13.68 NaN 4.79 2.88
2015-01-29 20.20 13.39 NaN 4.71 2.88
2015-01-30 20.96 13.66 NaN 4.77 2.95
2015-02-02 20.53 13.32 NaN 4.74 2.88
2015-02-03 20.15 13.11 NaN 4.82 2.86
2015-02-04 19.70 13.11 NaN 4.76 2.85
2015-02-05 19.54 12.88 NaN 4.62 2.85
2015-02-06 18.73 12.57 NaN 4.45 2.79
2015-02-09 18.42 12.76 NaN 4.48 2.79
2015-02-10 18.71 12.81 NaN 4.46 2.84
2015-02-11 18.61 12.93 NaN 4.58 2.85
2015-02-12 18.89 12.77 NaN 4.72 2.87
2015-02-13 19.10 12.90 NaN 4.77 2.90
... ... ... ... ... ...
2015-11-20 21.47 17.72 22.76 8.83 11.35
2015-11-23 21.12 17.24 21.52 9.16 11.35
2015-11-24 21.23 17.56 22.62 9.11 11.35
2015-11-25 21.37 17.80 22.76 9.15 11.35
2015-11-26 20.80 17.26 23.94 9.26 11.35
2015-11-27 19.22 15.84 21.73 8.51 11.35
2015-11-30 19.04 15.76 23.47 8.34 11.35
2015-12-01 19.26 16.02 23.22 8.71 11.35
2015-12-02 19.43 16.18 22.14 8.65 11.35
2015-12-03 19.61 16.28 23.41 8.73 11.35
2015-12-04 20.05 16.62 24.51 8.80 10.22
2015-12-07 19.70 16.46 23.97 8.73 9.20
2015-12-08 19.10 15.86 24.63 8.58 9.28
2015-12-09 18.70 15.65 23.14 8.23 8.36
2015-12-10 18.83 15.75 22.66 8.09 8.50
2015-12-11 18.62 15.84 22.40 7.87 8.02
2015-12-14 19.02 16.04 22.98 8.10 8.06
2015-12-15 19.04 16.08 22.64 8.15 8.14
2015-12-16 18.99 16.01 23.58 8.73 8.43
2015-12-17 19.92 16.43 24.68 8.96 8.47
2015-12-18 20.84 16.72 23.97 8.80 8.19
2015-12-21 21.62 17.04 24.44 8.84 8.21
2015-12-22 23.78 18.30 25.54 9.26 8.24
2015-12-23 23.55 17.47 25.47 8.93 8.03
2015-12-24 24.45 17.82 25.99 8.91 7.94
2015-12-25 24.39 17.60 24.92 9.03 7.95
2015-12-28 23.42 16.79 23.48 8.79 7.88
2015-12-29 23.63 16.89 23.80 8.80 7.78
2015-12-30 23.17 16.88 23.73 8.93 7.75
2015-12-31 23.23 16.68 22.91 8.74 7.41
300511.XSHE 600108.XSHG 600313.XSHG 600354.XSHG 600359.XSHG \
2015-01-05 NaN 9.51 4.50 8.81 10.92
2015-01-06 NaN 9.75 4.62 8.75 11.08
2015-01-07 NaN 9.98 4.70 8.85 11.07
2015-01-08 NaN 9.77 4.74 8.89 11.12
2015-01-09 NaN 9.41 4.59 8.60 10.80
2015-01-12 NaN 9.45 4.58 8.47 10.73
2015-01-13 NaN 9.50 4.69 8.78 10.90
2015-01-14 NaN 9.45 4.62 8.64 10.88
2015-01-15 NaN 9.56 4.66 8.65 11.11
2015-01-16 NaN 10.00 4.80 8.80 11.25
2015-01-19 NaN 9.66 4.72 8.42 10.79
2015-01-20 NaN 10.02 4.95 8.59 11.10
2015-01-21 NaN 10.23 5.24 8.84 11.29
2015-01-22 NaN 10.41 5.44 9.18 11.58
2015-01-23 NaN 10.09 5.39 8.98 11.36
2015-01-26 NaN 10.13 5.49 9.08 11.49
2015-01-27 NaN 10.44 5.89 9.37 11.73
2015-01-28 NaN 10.17 5.66 9.24 11.54
2015-01-29 NaN 10.06 5.67 9.36 11.24
2015-01-30 NaN 10.25 5.73 9.40 11.34
2015-02-02 NaN 9.64 5.32 8.93 11.31
2015-02-03 NaN 9.44 5.37 8.74 11.13
2015-02-04 NaN 9.22 5.17 8.60 10.87
2015-02-05 NaN 8.96 5.11 8.44 10.70
2015-02-06 NaN 8.57 4.92 8.14 10.35
2015-02-09 NaN 8.63 5.28 8.18 10.33
2015-02-10 NaN 8.69 5.43 8.25 10.27
2015-02-11 NaN 8.80 5.74 8.28 10.61
2015-02-12 NaN 8.75 5.70 8.20 10.57
2015-02-13 NaN 8.88 5.66 8.34 10.71
... ... ... ... ... ...
2015-11-20 NaN 7.72 5.78 8.95 13.02
2015-11-23 NaN 7.72 5.79 8.94 12.60
2015-11-24 NaN 7.77 5.87 9.20 12.46
2015-11-25 NaN 7.82 6.16 9.71 12.78
2015-11-26 NaN 7.85 5.94 9.44 12.70
2015-11-27 NaN 7.15 5.60 8.83 13.05
2015-11-30 NaN 7.07 5.62 9.34 14.05
2015-12-01 NaN 7.41 6.14 9.49 13.60
2015-12-02 NaN 7.45 6.07 9.51 13.07
2015-12-03 NaN 7.48 6.28 9.67 13.40
2015-12-04 NaN 7.77 6.60 10.08 13.83
2015-12-07 NaN 7.83 6.59 10.16 13.60
2015-12-08 NaN 7.44 6.14 9.81 13.40
2015-12-09 NaN 7.29 6.00 9.59 13.07
2015-12-10 NaN 7.26 6.02 10.23 12.94
2015-12-11 NaN 7.20 6.01 9.83 12.27
2015-12-14 NaN 7.35 6.11 9.88 12.56
2015-12-15 NaN 7.37 6.14 9.88 12.43
2015-12-16 NaN 7.31 6.09 9.88 12.75
2015-12-17 NaN 7.48 6.31 9.88 13.09
2015-12-18 NaN 7.57 6.39 9.88 12.91
2015-12-21 NaN 7.70 6.38 9.88 13.18
2015-12-22 NaN 7.80 6.53 9.88 13.66
2015-12-23 NaN 7.58 6.23 9.88 13.02
2015-12-24 NaN 7.87 6.28 9.88 13.05
2015-12-25 NaN 7.80 6.20 9.88 12.80
2015-12-28 NaN 7.45 5.88 9.88 12.44
2015-12-29 NaN 7.50 6.06 9.88 12.49
2015-12-30 NaN 7.46 6.06 9.88 12.51
2015-12-31 NaN 7.32 6.00 9.88 11.96
600371.XSHG 600506.XSHG 600540.XSHG 600598.XSHG 601118.XSHG
2015-01-05 10.55 11.33 6.28 9.34 8.88
2015-01-06 10.72 11.62 6.39 9.65 9.15
2015-01-07 10.70 11.54 6.37 9.68 9.03
2015-01-08 10.76 11.81 6.39 9.70 8.85
2015-01-09 10.47 11.73 6.30 9.58 8.61
2015-01-12 10.27 11.34 6.22 9.57 8.89
2015-01-13 10.40 11.54 6.25 9.59 8.94
2015-01-14 10.35 11.84 6.29 9.34 8.75
2015-01-15 10.45 11.86 6.37 9.51 8.90
2015-01-16 10.63 11.98 6.42 9.65 9.09
2015-01-19 10.35 11.96 6.26 9.27 8.60
2015-01-20 10.65 12.33 6.39 9.62 8.80
2015-01-21 10.85 12.65 6.53 9.94 8.94
2015-01-22 11.07 12.76 6.65 10.19 9.25
2015-01-23 10.84 12.62 6.59 10.04 9.06
2015-01-26 11.02 12.74 6.79 10.49 9.20
2015-01-27 11.11 12.79 6.94 10.65 9.34
2015-01-28 10.89 12.61 6.92 10.57 9.15
2015-01-29 10.78 12.32 6.89 10.50 9.04
2015-01-30 11.11 12.26 6.84 10.56 9.14
2015-02-02 11.15 12.22 6.87 10.03 8.81
2015-02-03 10.93 12.37 7.10 9.93 8.73
2015-02-04 11.12 12.45 6.83 9.85 8.64
2015-02-05 11.02 12.18 6.69 9.72 8.37
2015-02-06 10.69 11.88 6.54 9.52 7.93
2015-02-09 10.50 11.85 6.46 9.59 8.01
2015-02-10 10.55 11.85 6.49 9.56 8.04
2015-02-11 10.56 11.98 6.66 9.87 8.18
2015-02-12 10.87 12.08 6.70 10.13 8.14
2015-02-13 10.95 12.29 6.85 10.14 8.23
... ... ... ... ... ...
2015-11-20 17.25 21.69 8.39 14.07 7.75
2015-11-23 17.61 21.15 8.16 14.08 7.86
2015-11-24 17.90 21.18 8.36 14.19 7.98
2015-11-25 18.93 21.28 8.67 14.48 7.98
2015-11-26 18.96 21.55 8.84 14.31 8.15
2015-11-27 19.33 19.49 8.64 13.19 7.43
2015-11-30 21.26 19.05 8.35 12.77 7.29
2015-12-01 20.77 19.81 8.69 13.35 7.68
2015-12-02 20.04 19.26 8.39 13.39 7.74
2015-12-03 20.63 20.69 8.51 13.45 7.82
2015-12-04 21.81 20.70 8.77 14.35 8.15
2015-12-07 21.74 20.94 8.82 14.73 8.15
2015-12-08 20.32 20.95 8.45 13.87 7.70
2015-12-09 20.32 20.53 8.23 13.36 7.68
2015-12-10 19.58 21.12 8.12 13.61 7.58
2015-12-11 20.09 21.12 8.18 13.25 7.46
2015-12-14 20.68 21.29 8.23 13.43 7.63
2015-12-15 20.69 21.76 8.31 13.55 7.67
2015-12-16 21.94 22.07 8.32 13.45 7.54
2015-12-17 22.14 22.82 8.68 14.11 7.70
2015-12-18 21.59 23.35 9.03 14.21 7.80
2015-12-21 21.35 22.92 8.92 14.36 7.97
2015-12-22 23.49 23.10 8.89 14.79 8.14
2015-12-23 22.48 22.87 8.71 14.17 7.90
2015-12-24 22.97 23.60 8.75 14.53 8.11
2015-12-25 23.06 24.05 9.13 14.46 8.03
2015-12-28 22.28 22.30 9.04 13.71 7.68
2015-12-29 22.31 22.71 9.05 13.80 7.74
2015-12-30 22.42 22.62 8.79 13.70 7.70
2015-12-31 22.27 23.43 8.46 13.53 7.56
[244 rows x 15 columns]
<matplotlib.legend.Legend at 0x7f2560de19e8>
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