Customization for pandas dataframe.

Author: bcottman

.DS_Store

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+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

.idea/.gitignore

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+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

.idea/FinMrkt.iml

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+# !/usr/bin/env python
+# -*- coding: utf-8 -*-
+__coverage__ = 0.0
+__author__ = "Bruce_H_Cottman"
+__license__ = "MIT License"
+import warnings
+
+warnings.filterwarnings("ignore")
+
+import math
+from pandas import to_datetime
+from statistics import stdev
+from pandas_datareader.data import DataReader
+
+
+### pasoDecorators class
+# adapted from pandas-flavor 11/13/2019
+from pandas.api.extensions import register_dataframe_accessor
+from functools import wraps
+
+from pandas.core.dtypes.generic import ABCDataFrame
+def register_DataFrame_method(method):
+    """Register a function as a method attached to the Pandas DataFrame.
+    Example
+    -------
+    for a function
+        @pf.register_dataframe_method
+        def row_by_value(df, col, value):
+        return df[df[col] == value].squeeze()
+
+    for a class method
+        @pf.register_dataframe_accessor('Aclass')
+        class Aclass(object):
+
+        def __init__(self, data):
+        self._data
+
+        def row_by_value(self, col, value):
+            return self._data[self._data[col] == value].squeeze()
+    """
+
+    def inner(*args, **kwargs):
+        class AccessorMethod(object):
+            def __init__(self, pandas_obj):
+                self._obj = pandas_obj
+
+            @wraps(method)
+            def __call__(self, *args, **kwargs):
+                return method(self._obj, *args, **kwargs)
+
+        register_dataframe_accessor(method.__name__)(AccessorMethod)
+        return method
+
+    return inner()
+
+
+def FutureValue_(principle=0, deposit=0, withdrawal=0, return_=0, nperiod=1):
+    if (principle + deposit + withdrawal) == 0:
+        return 0
+    if return_ <= 0:
+        return principle + deposit + withdrawal  # default is end of period
+    amount = deposit - withdrawal
+    cumamount = 0
+    for n in range(1, nperiod + 1):
+        #        print( 'before cumamount',cumamount)
+        cumamount = cumamount + deposit * (1 + return_) ** n
+    #        print( 'after cumamount',cumamount)
+    return principle * (1 + return_ ** nperiod) + cumamount
+
+
+def nppy_(EFT_df):
+    t_dayspy = 252
+    t_weekspy = 53
+    t_monthsspy = 12
+    t_ypy = 1
+
+    nlen = len(EFT_df.index.day)
+    ndays = ((EFT_df.index[-1] - EFT_df.index[0])).days + 1
+    nweeks = ndays // 7
+    nmonths = ndays // 30.5
+    if ndays >= nlen:
+        return t_dayspy
+    elif ndays >= nlen:
+        return t_monthsspy
+    elif nlen >= nmonths:
+        return t_monthsspy
+    elif nlen >= nweeks:
+        return t_weekspy
+    else:
+        return t_ypy
+
+
+def p_or_r_std(
+    asset_value_type, EFT_df, column_name, ticker, rd_type, start_date, end_date
+):
+    EFT_df = DataReader(ticker, rd_type, start=start_date, end=end_date)
+    EFT_df.index = to_datetime(EFT_df.index, format="%Y-%m-%d")
+    nppy = nppy_(EFT_df)
+    if asset_value_type.lower() == "price":
+
+        ave_price = EFT_df[column_name].mean()
+        return (ave_price * nppy, statistics.stdev(EFT_df[column_name]))
+    else:
+        EFT_df["return"] = (
+            EFT_df[column_name] - EFT_df[column_name].shift(1)
+        ) / EFT_df[column_name].shift(1)
+
+        ave_return = (EFT_df["return"]).mean(skipna=True)
+
+        return (ave_return * nppy, EFT_df["return"].std(skipna=True))
+
+
+def return_fit(nperiod: int = 1, principle: float = 0.0, return_: float = 0.0) -> float:
+    if (principle) == 0:
+        return 0
+    if return_ <= 0:
+        return principle  # default is end of period
+    return principle * (1 + return_) ** nperiod
+
+
+def price_std(EFT_df, column_name, ticker, rd_type, start_date, end_date):
+
+    EFT_df = DataReader(ticker, rd_type, start=start_date, end=end_date)
+    EFT_df.index = to_datetime(EFT_df.index, format="%Y-%m-%d")
+
+    return stdev(EFT_df[column_name])

.idea/encodings.xml

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+cpdef int count_primes(int limit):  
+  cdef int count = 0
+  cdef int candidate_int
+  cdef int factor
+  for candidate_int in range(limit):
+    if (candidate_int > 1):
+      for factor in range(2, candidate_int):
+        if (candidate_int % factor == 0):
+           break
+        else:
+           count += 1
+  return count