多只股票价格统计分析问题

Question

原数据是按日期由近到远统计的多个股票的每日价格信息。请解决如下问题：
一、添加两列分别求出五日、十日移动均价：
二、添加一列求出前两日的五日移动均价：
三、添加一列计算观察期30天内股票的最大涨幅：
PS：有些股票可能某人有重复记录需要剔除重复部分
附件为股票信息：
ts_code trade_date close
34 300025.SZ 20211027 3.51
46 300022.SZ 20211027 4
51 300019.SZ 20211027 19.63
72 300016.SZ 20211027 8.23
91 300017.SZ 20211027 5.37
95 300030.SZ 20211027 8.65
111 300025.SZ 20211026 3.63
119 300030.SZ 20211026 8.99
142 300017.SZ 20211026 5.57
163 300016.SZ 20211026 8.47
179 300022.SZ 20211026 4.11
189 300019.SZ 20211026 19.78
192 300030.SZ 20211025 9.01
209 300017.SZ 20211025 5.56
179 300022.SZ 20211026 4.11
189 300019.SZ 20211026 19.78
192 300030.SZ 20211025 9.01
209 300017.SZ 20211025 5.56
224 300016.SZ 20211025 8.4
265 300025.SZ 20211025 3.7
270 300019.SZ 20211025 19.9
278 300022.SZ 20211025 4.19
288 300022.SZ 20211022 4.21
304 300025.SZ 20211022 3.68
333 300019.SZ 20211022 19.73
335 300030.SZ 20211022 9.13
355 300016.SZ 20211022 8.41
374 300017.SZ 20211022 5.58
386 300030.SZ 20211021 9.13
437 300016.SZ 20211021 8.44
440 300025.SZ 20211021 3.75
463 300017.SZ 20211021 5.59
465 300022.SZ 20211021 4.24
469 300019.SZ 20211021 20.53
463 300017.SZ 20211021 5.59
465 300022.SZ 20211021 4.24
469 300019.SZ 20211021 20.53
490 300016.SZ 20211020 8.61
502 300017.SZ 20211020 5.75
504 300022.SZ 20211020 4.33
511 300025.SZ 20211020 3.82
562 300019.SZ 20211020 20.28
569 300030.SZ 20211020 9.22
589 300016.SZ 20211019 8.7
599 300019.SZ 20211019 19.57
602 300030.SZ 20211019 9.37
606 300025.SZ 20211019 3.89
621 300017.SZ 20211019 5.88
653 300022.SZ 20211019 4.41
691 300030.SZ 20211018 9.33
698 300016.SZ 20211018 8.65
706 300019.SZ 20211018 19.47
707 300022.SZ 20211018 4.45
724 300025.SZ 20211018 3.96
745 300017.SZ 20211018 5.82
777 300025.SZ 20211015 3.95
817 300030.SZ 20211015 9.5
824 300016.SZ 20211015 8.64
840 300017.SZ 20211015 5.8
843 300019.SZ 20211015 19.09
844 300022.SZ 20211015 4.43
866 300017.SZ 20211014 5.85
889 300030.SZ 20211014 9.65
894 300019.SZ 20211014 18.9
939 300022.SZ 20211014 4.54
960 300016.SZ 20211014 8.97
961 300025.SZ 20211014 3.96
963 300016.SZ 20211013 9.04
965 300019.SZ 20211013 18.11
999 300017.SZ 20211013 5.91
1014 300025.SZ 20211013 4.02
1035 300022.SZ 20211013 4.55
1045 300030.SZ 20211013 9.69
1070 300025.SZ 20211012 4
1073 300022.SZ 20211012 4.54
1100 300017.SZ 20211012 5.86
1107 300016.SZ 20211012 9.02
1113 300030.SZ 20211012 9.65
1130 300019.SZ 20211012 18.53
1172 300030.SZ 20211011 9.79
1187 300019.SZ 20211011 18.2
1188 300022.SZ 20211011 4.69
1219 300017.SZ 20211011 5.92
1240 300016.SZ 20211011 9.1
1245 300025.SZ 20211011 4
1258 300025.SZ 20211008 4
1260 300022.SZ 20211008 4.79
1292 300030.SZ 20211008 9.87
1308 300017.SZ 20211008 5.93
1312 300019.SZ 20211008 18.31
1334 300016.SZ 20211008 9.28
1355 300017.SZ 20210930 5.76
1356 300019.SZ 20210930 18.63
1369 300016.SZ 20210930 8.86
1371 300025.SZ 20210930 3.86
1411 300022.SZ 20210930 4.58
1426 300030.SZ 20210930 9.71
1450 300017.SZ 20210929 5.68
1475 300016.SZ 20210929 8.76
1477 300022.SZ 20210929 4.46
1496 300019.SZ 20210929 17.76
1511 300030.SZ 20210929 9.65
1527 300025.SZ 20210929 3.75
1541 300022.SZ 20210928 4.62
1549 300030.SZ 20210928 9.93
1561 300017.SZ 20210928 5.94
1574 300025.SZ 20210928 3.83
1611 300016.SZ 20210928 9.2
1631 300019.SZ 20210928 18.84
1643 300019.SZ 20210927 18.75
1644 300025.SZ 20210927 3.75
1679 300017.SZ 20210927 5.95
1688 300022.SZ 20210927 4.47
1700 300016.SZ 20210927 9.24
1701 300030.SZ 20210927 10
1745 300022.SZ 20210924 4.88
1750 300019.SZ 20210924 19.99
1755 300016.SZ 20210924 9.54
1794 300025.SZ 20210924 3.91
1802 300030.SZ 20210924 10.3
1819 300017.SZ 20210924 6.11
1855 300022.SZ 20210923 5.18
1863 300030.SZ 20210923 10.15
1871 300017.SZ 20210923 6.3
1880 300019.SZ 20210923 20.81
1889 300016.SZ 20210923 9.75
1902 300025.SZ 20210923 4.07
1922 300030.SZ 20210922 10.15
1969 300022.SZ 20210922 4.95
1979 300016.SZ 20210922 9.48
1993 300025.SZ 20210922 3.97
2008 300017.SZ 20210922 6.24
2014 300019.SZ 20210922 22.14
2022 300025.SZ 20210917 4.03
2024 300016.SZ 20210917 9.52
2067 300019.SZ 20210917 21.87
2076 300022.SZ 20210917 5.02
2087 300030.SZ 20210917 10.14
2101 300017.SZ 20210917 6.3
2118 300030.SZ 20210916 9.92
2127 300016.SZ 20210916 9.36
2139 300017.SZ 20210916 6.43
2177 300025.SZ 20210916 4.09
2192 300019.SZ 20210916 21.67
2204 300022.SZ 20210916 5.17
2213 300022.SZ 20210915 5.21
2224 300030.SZ 20210915 9.94
2235 300016.SZ 20210915 9.67
2247 300017.SZ 20210915 6.64
2285 300025.SZ 20210915 4.19
2293 300019.SZ 20210915 23.51
2313 300025.SZ 20210914 4.16
2324 300019.SZ 20210914 24.6
2347 300022.SZ 20210914 5.16
2353 300016.SZ 20210914 9.5
2362 300030.SZ 20210914 10.08
2378 300017.SZ 20210914 6.34
2420 300019.SZ 20210913 24.66
2431 300030.SZ 20210913 10.21
2436 300025.SZ 20210913 4.26
2470 300017.SZ 20210913 6.48
2490 300022.SZ 20210913 5.07
2496 300016.SZ 20210913 9.39
2512 300025.SZ 20210910 4.34
2518 300022.SZ 20210910 5.07
2520 300019.SZ 20210910 23.57
2544 300016.SZ 20210910 9.24
2555 300030.SZ 20210910 10.06
2572 300017.SZ 20210910 6.35
2596 300017.SZ 20210909 6.45
2597 300030.SZ 20210909 10.17
2636 300019.SZ 20210909 22.69
2653 300025.SZ 20210909 4.42
2670 300022.SZ 20210909 5.12
2675 300016.SZ 20210909 9.34
2693 300016.SZ 20210908 9.33
2710 300022.SZ 20210908 5.15
2719 300025.SZ 20210908 4.46
2723 300017.SZ 20210908 6.33
2733 300030.SZ 20210908 10.25
2763 300019.SZ 20210908 23.53
2790 300019.SZ 20210907 24.42
2811 300025.SZ 20210907 4.29
2812 300030.SZ 20210907 10.25
2829 300022.SZ 20210907 5.21
2851 300017.SZ 20210907 6.07
2872 300016.SZ 20210907 9.39
2907 300016.SZ 20210906 9.38
2916 300025.SZ 20210906 4.29
2951 300017.SZ 20210906 6.06
2962 300019.SZ 20210906 24.24
2968 300022.SZ 20210906 5.27
2983 300030.SZ 20210906 10.26
2984 300016.SZ 20210903 9.18
2985 300022.SZ 20210903 5.14
2992 300017.SZ 20210903 6.03
3015 300019.SZ 20210903 26.24
3041 300025.SZ 20210903 4.24
3074 300030.SZ 20210903 10.25
3097 300017.SZ 20210902 5.98
3098 300025.SZ 20210902 4.2
3117 300016.SZ 20210902 8.89
3118 300019.SZ 20210902 25.74
3126 300030.SZ 20210902 9.97
3150 300022.SZ 20210902 5.15
3182 300030.SZ 20210901 9.93
3195 300017.SZ 20210901 5.97
3231 300019.SZ 20210901 25.31
3250 300016.SZ 20210901 8.67
3251 300022.SZ 20210901 5.25
3259 300025.SZ 20210901 4.28
3323 300017.SZ 20210831 5.92
3328 300022.SZ 20210831 5.42
3335 300019.SZ 20210831 28.58
3342 300016.SZ 20210831 8.52
3359 300030.SZ 20210831 9.87
3370 300025.SZ 20210831 4.19
3382 300019.SZ 20210830 27.53
3402 300025.SZ 20210830 4.22
3411 300016.SZ 20210830 8.53
3415 300022.SZ 20210830 5.39
3463 300030.SZ 20210830 9.96
3466 300017.SZ 20210830 6.15
3474 300022.SZ 20210827 5.09
3504 300017.SZ 20210827 6.13
3508 300025.SZ 20210827 4.29
3524 300019.SZ 20210827 29.35
3530 300016.SZ 20210827 8.6
3556 300030.SZ 20210827 10.03
3588 300030.SZ 20210826 10.16
3592 300019.SZ 20210826 29.6
3617 300016.SZ 20210826 8.75
3630 300022.SZ 20210826 5.15
3652 300017.SZ 20210826 6.12
3657 300025.SZ 20210826 4.42
3663 300022.SZ 20210825 5.37
3667 300016.SZ 20210825 8.97
3678 300019.SZ 20210825 28.49
3686 300025.SZ 20210825 4.55
3747 300017.SZ 20210825 6.19
3748 300030.SZ 20210825 10.31
3771 300016.SZ 20210824 8.98
3783 300017.SZ 20210824 6.19
3787 300019.SZ 20210824 25.08
3803 300030.SZ 20210824 10.14
3814 300022.SZ 20210824 5.16
3815 300025.SZ 20210824 4.53
3859 300022.SZ 20210823 4.99
3884 300016.SZ 20210823 8.89
3897 300017.SZ 20210823 6.33
3909 300019.SZ 20210823 25.86
3940 300030.SZ 20210823 10.14
3942 300025.SZ 20210823 4.62
3967 300022.SZ 20210820 4.56
3990 300025.SZ 20210820 4.71
3992 300030.SZ 20210820 10.05
4003 300016.SZ 20210820 8.91
4033 300017.SZ 20210820 6.29
4049 300019.SZ 20210820 23.83
4074 300025.SZ 20210819 4.72
4086 300019.SZ 20210819 23.55
4090 300030.SZ 20210819 10.13
4119 300017.SZ 20210819 6.4
4143 300016.SZ 20210819 8.95
4146 300022.SZ 20210819 4.61
4175 300022.SZ 20210818 4.69
4190 300016.SZ 20210818 8.66
4217 300017.SZ 20210818 6.2
4228 300025.SZ 20210818 4.31
4229 300030.SZ 20210818 10.22
4235 300019.SZ 20210818 21.19
4270 300017.SZ 20210817 6.28
4271 300025.SZ 20210817 4.23
4292 300022.SZ 20210817 4.71
4298 300030.SZ 20210817 10.07
4326 300019.SZ 20210817 19.88
4333 300016.SZ 20210817 8.57
4361 300019.SZ 20210816 22.15
4396 300017.SZ 20210816 6.12
4409 300030.SZ 20210816 10.42
4410 300025.SZ 20210816 4.42
4421 300016.SZ 20210816 8.9
4436 300022.SZ 20210816 4.87
4439 300017.SZ 20210813 6.1
4442 300025.SZ 20210813 4.5
4446 300030.SZ 20210813 10.43
4456 300016.SZ 20210813 8.76
4467 300019.SZ 20210813 21.9
4475 300022.SZ 20210813 4.95
4574 300016.SZ 20210812 8.75
4592 300017.SZ 20210812 6.23
4609 300025.SZ 20210812 4.6
4610 300030.SZ 20210812 10.49
4613 300019.SZ 20210812 20.98
4628 300022.SZ 20210812 5
4638 300017.SZ 20210811 6.11
4640 300025.SZ 20210811 4.49
4669 300030.SZ 20210811 10.47
4705 300016.SZ 20210811 8.72
4707 300019.SZ 20210811 21.74
4711 300022.SZ 20210811 5.08
4741 300017.SZ 20210810 6.18
4760 300025.SZ 20210810 4.49
4794 300030.SZ 20210810 10.67
4802 300016.SZ 20210810 8.74
4803 300019.SZ 20210810 21.32
4814 300022.SZ 20210810 5
4827 300016.SZ 20210809 8.66
4829 300019.SZ 20210809 21.74
4843 300025.SZ 20210809 4.4
4855 300022.SZ 20210809 4.92
4861 300017.SZ 20210809 6.2
4883 300030.SZ 20210809 10.61
4924 300019.SZ 20210806 21.7
4965 300017.SZ 20210806 6.27
4976 300016.SZ 20210806 8.67
4981 300030.SZ 20210806 10.61

Answer 1

需要先对数据框进行排序整理，使用rolling函数设置窗口大小及窗口内元素数量。参考如下代码

import pandas as pd

pd.set_option('display.max_rows',None)
df=pd.read_csv('stock_info.csv',sep='\s',engine='python')
df=df.drop_duplicates()
df=df.sort_values(by=['ts_code','trade_date'])

n=sorted(set(df['ts_code']))
a=[]
b=[]
for code in n:
    a+=df.loc[df['ts_code']==code]['close'].rolling(5,min_periods=1).mean().tolist()
    b+=df.loc[df['ts_code'] == code]['close'].rolling(10,min_periods=1).mean().tolist()
df['m5']=a
df['m10']=b
print(df)