模塊：Numpy

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準備工作：

抓取某一只股票的信息，每30min為一組數據，可以參考上一篇：

Note: 只為演示如何統計，更精準的可以抓取每5min為一組數據

PS：如有需要Python學習資料的小伙伴可以加點擊下方鏈接自行獲取

目標：輸出每天的開盤，收盤，最高，最低價格，以其中的某一周(5 days, 40組數據)為例

1， 從csv中導入數據，需要有 open, high, close 和low

#import numpy as np

open = np.loadtxt('30min.csv', dtype = float, skiprows = 1, usecols = 2, delimiter=',', encoding = 'utf-8')

high = np.loadtxt('30min.csv', dtype = float, skiprows = 1, usecols = 3, delimiter=',', encoding = 'utf-8')

close = np.loadtxt('30min.csv', dtype = float, skiprows = 1, usecols = 4, delimiter=',', encoding = 'utf-8')

low = np.loadtxt('30min.csv', dtype = float, skiprows = 1, usecols = 5, delimiter=',', encoding = 'utf-8')

打印測試可以得到如下數據，

2，從csv中導入date數據，需要將date轉化輸出成工作日的格式

from datetime import datetime

def datestr(s):

return datetime.strptime(s, '%Y/%m/%d').isoweekday()

#print(datestr('2020/12/7'))

dates = np.loadtxt('30min.csv',dtype = str, skiprows = 1, usecols = 0, converters = {0: datestr}, delimiter = ',', encoding = 'utf-8')

打印測試可以得到如下數據，

3， 找到某一周的40組數據，確認第一天的開盤時間和最后一天的收盤時間

close = close[0:40]

dates = dates[0:40]

first_monday = np.ravel(np.where(dates == 1))[-1] #根據csv中的排序找到某一周的第一天

last_friday = np.ravel(np.where(dates == 5))[0] #根據csv中的排序找到某一周的最后一天

打印測試得到如下某一周的40個時間

4， 創建一個數組，用于存儲一周內每一天的索引值

day_indices = np.arange(last_friday, first_monday +1)[::-1]

weeks_indices = np.split(day_indices, 5)

打印測試得到如下輸出，

5，編寫summarize函數，返回一個元組包含這一周每天對應的open, close, high, low

def summarize(a, o, h, c, l):

monday_open = o[a[0]]? #monday open是最后一個價格

day_high = np.max( np.take(h, a) )? #每天的最高價格

day_low = np.min( np.take(l, a) )#每天的最低價格

friday_close = c[a[-1]]? #friday close是第一個價格

return('lux', monday_open, day_high, friday_close, day_low)

6，生成每周的數據

weeksummary = np.apply_along_axis(summarize, 1, weeks_indices, open, high, close, low)

print(' ****** open,? high,? close,? low \n', weeksummary)

對比一下表格中的數據信息，結果是匹配的

7， 如果有需要可以保存

np.savetxt('cw36_lux.csv', weeksummary, delimiter = ',', fmt = '%s') #同30min.csv在同一文件夾下

打開csv之后保存的數據如下

好了，完整的代碼如下：

import numpy as np

from datetime import datetime

def datestr(s):

return datetime.strptime(s, '%Y/%m/%d').isoweekday()

dates, open, high, close, low = np.loadtxt('30min.csv', skiprows = 1, usecols = (0, 2, 3, 4, 5), converters = {0:datestr}, delimiter = ',', unpack = True, encoding = 'utf-8')

close = close[0:40]

dates = dates[0:40]

#print(dates)

first_monday = np.ravel(np.where(dates == 1))[-1]

#print(first_monday)

last_friday = np.ravel(np.where(dates == 5))[0]

#print(last_friday)

day_indices = np.arange(last_friday, first_monday +1)[::-1]

#print(day_indices)

weeks_indices = np.split(day_indices, 5)

#print(weeks_indices)

def summarize(a, o, h, c, l):

monday_open = o[a[0]]

day_high = np.max( np.take(h, a) )

day_low = np.min( np.take(l, a) )

friday_close = c[a[-1]]

return('lux', monday_open, day_high, friday_close, day_low)

weeksummary = np.apply_along_axis(summarize, 1, weeks_indices, open, high, close, low)

#print(' ****** open,? high,? close,? low \n', weeksummary)

np.savetxt('cw36_lux.csv', weeksummary, delimiter = ',', fmt = '%s')

歡迎大家一起討論學習。

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