Automated formatting changes

example/Example-Analysis.py

@@ -9,10 +9,11 @@
 
 # <codecell>
 
+import datetime
 import pathlib
+
 import matplotlib.pyplot as plt
 import pandas as pd
-import datetime
 
 # importing FinQuant's function to automatically build the portfolio
 from finquant.portfolio import build_portfolio

example/Example-Build-Portfolio-from-file.py

@@ -9,9 +9,10 @@
 
 # <codecell>
 
+import datetime
 import pathlib
+
 import pandas as pd
-import datetime
 
 # importing FinQuant's function to automatically build the portfolio
 from finquant.portfolio import build_portfolio

example/Example-Build-Portfolio-from-web.py

@@ -9,9 +9,10 @@
 
 # <codecell>
 
-import pandas as pd
 import datetime
 
+import pandas as pd
+
 # importing some custom functions/objects
 from finquant.portfolio import build_portfolio
 

example/Example-Optimisation.py

@@ -26,11 +26,12 @@
 
 # <codecell>
 
+import datetime
 import pathlib
+
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
-import datetime
 
 # importing FinQuant's function to automatically build the portfolio
 from finquant.portfolio import build_portfolio

finquant/asset.py

@@ -45,7 +45,9 @@ class Asset:
 
     """
 
-    def __init__(self, data: pd.Series, name: str, asset_type: str = 'Market index') -> None:
+    def __init__(
+        self, data: pd.Series, name: str, asset_type: str = "Market index"
+    ) -> None:
         """
         :Input:
          :data: ``pandas.Series``, of asset prices
@@ -119,4 +121,4 @@ def properties(self):
     def __str__(self):
         # print short description
         string = f"Contains information about {self.asset_type}: {self.name}."
-        return string
+        return string

finquant/market.py

@@ -14,6 +14,7 @@
 
 import numpy as np
 import pandas as pd
+
 from finquant.asset import Asset
 from finquant.returns import daily_returns, historical_mean_return
 
@@ -43,4 +44,4 @@ def comp_daily_returns(self) -> pd.Series:
         """Computes the daily returns (percentage change) of the market index.
         See ``finquant.returns.daily_returns``.
         """
-        return daily_returns(self.data)
+        return daily_returns(self.data)

finquant/portfolio.py

@@ -48,8 +48,8 @@
 - Individual stocks of the portfolio (Expected Return over Volatility)
 """
 
-from typing import List
 import datetime
+from typing import List
 
 import matplotlib.pylab as plt
 import numpy as np

finquant/stock.py

@@ -25,6 +25,7 @@
 
 import numpy as np
 import pandas as pd
+
 from finquant.asset import Asset
 from finquant.returns import daily_returns, historical_mean_return
 
@@ -45,7 +46,6 @@ class Stock(Asset):
 
     """
 
-
     def __init__(self, investmentinfo: pd.DataFrame, data: pd.Series) -> None:
         """
         :Input:
@@ -93,4 +93,4 @@ def properties(self):
         string += "\nInformation:"
         string += "\n" + str(self.investmentinfo.to_frame().transpose())
         string += "\n" + "-" * 50
-        print(string)
+        print(string)