add day16 homework

Author: alvinhuu

D16_timePeriod/homework.py

@@ -0,0 +1,12 @@
+import pandas as pd  
+import numpy as np
+
+# 題目：運下列時間序列資料做運算
+index = pd.date_range("1/1/2021", periods=20, freq='D')
+series = pd.Series(range(20), index=index)
+# print(f'index= {index}')
+print(series)
+# 將所有轉為周資料
+print( series.resample('W',convention='start').asfreq('D') )
+# 將周資料的值取平均
+print( series.resample('W').mean() )

Stock/LPPLS_Bubble.py

@@ -0,0 +1,14 @@
+import pandas as pd  
+import numpy as np
+import urllib3
+# from bs4 import BeautifulSoup
+import yfinance as yf
+import matplotlib.pyplot as plt
+import lppls
+
+# 參考網站 https://colab.research.google.com/drive/1oEMk8-yvhaWHP9DwE6bO_uzazPcvEvAY?usp=sharing
+# 中文 https://www.finlab.tw/bitcoin-stock-bubble-analysis-lppl/
+# Log Periodic Power Law Singularity (LPPLS) Model
+
+
+

Stock/Single.py

@@ -9,10 +9,8 @@
 # Yahoo! module
 #https://pypi.org/project/yfinance/
 # Get the data of the stock AAPL 
-print( yf.download('QS','2020-01-01','2021-03-01') )
-print( yf.download('ISR','2020-01-01','2021-03-01') )
-print( yf.download('SENS','2020-01-01','2021-03-01') )
-print( yf.download('NVIV','2020-01-01','2021-03-01') ) 
+print( yf.download('TLRY','2020-12-01','2021-03-01') )
+print( yf.download('APHA','2020-12-01','2021-03-01') )
 # # Plot the close price of the AAPL 
 # data.Close.plot() 
 # plt.show() 

Stock/TaiwanStock.py

@@ -0,0 +1,21 @@
+# 參考網站 https://www.finlab.tw/%e8%b6%85%e7%b0%a1%e5%96%ae%e5%8f%b0%e8%82%a1%e6%af%8f%e6%97%a5%e7%88%ac%e8%9f%b2%e6%95%99%e5%ad%b8/
+
+import requests
+from io import StringIO
+import pandas as pd
+import numpy as np
+
+datestr = '20200131'
+
+# 下載股價
+r = requests.post('https://www.twse.com.tw/exchangeReport/MI_INDEX?response=csv&date=' + datestr + '&type=ALL')
+
+# 整理資料，變成表格
+df = pd.read_csv(StringIO(r.text.replace("=", "")), 
+            header=["證券代號" in l for l in r.text.split("\n")].index(True)-1)
+
+# 整理一些字串：
+df = df.apply(lambda s: pd.to_numeric(s.astype(str).str.replace(",", "").replace("+", "1").replace("-", "-1"), errors='coerce'))
+
+# 顯示出來
+df.head()

Stock/top100.py

@@ -4,6 +4,8 @@
 # from bs4 import BeautifulSoup
 import yfinance as yf
 import matplotlib.pyplot as plt
+import time
+timestr = time.strftime("%Y%m%d-%H%M%S")
 
 # 參考網站
 # https://medium.com/ai%E8%82%A1%E4%BB%94/%E7%94%A8-python-%E6%89%93%E9%80%A0%E8%87%AA%E5%B7%B1%E7%9A%84%E8%82%A1%E5%B8%82%E8%B3%87%E6%96%99%E5%BA%AB-%E7%BE%8E%E8%82%A1%E7%AF%87-e3e896659fd6
@@ -26,6 +28,13 @@ def Money2int(x):
         return float(x)
     return (float(x[:-1]) * 10 ** m[x[-1]] )
 
+def over3(x):
+    A = Money2int(x[5])
+    B = Money2int(x[6])
+    P = p2f(x[4])
+    L = ( A>B and P>=0.03 )
+    return L
+
 def sort3to10(x):
     A = Money2int(x[5])
     B = Money2int(x[6])
@@ -50,5 +59,8 @@ def setFunc( func ):
 print(setFunc(big10))
 print(setFunc(sort3to10))
 
+Over3 = setFunc(over3)
+print(timestr)
+Over3.to_excel('over3.xlsx', sheet_name='A'+timestr)
 # data=data[np.argsort(data[:,0])]
 # stk_list = data.Symbol