from packer import Packer
from fdates import parse
P = Packer()
P.d_yfi(1, "NDQ.AX")
P.percentages(1, "close")
# P.percentages(1, "close")
# P.stacked(1, "close")
# P.d_fred(2, "https://fred.stlouisfed.org/graph/fredgraph.csv?bgcolor=%23e1e9f0&chart_type=line&drp=0&fo=open%20sans&graph_bgcolor=%23ffffff&height=450&mode=fred&recession_bars=on&txtcolor=%23444444&ts=12&tts=12&width=1168&nt=0&thu=0&trc=0&show_legend=yes&show_axis_titles=yes&show_tooltip=yes&id=OVXCLS&scale=left&cosd=2007-05-10&coed=2020-10-29&line_color=%234572a7&link_values=false&line_style=solid&mark_type=none&mw=3&lw=2&ost=-99999&oet=99999&mma=0&fml=a&fq=Daily%2C%20Close&fam=avg&fgst=lin&fgsnd=2020-02-01&line_index=1&transformation=lin&vintage_date=2020-10-31&revision_date=2020-10-31&nd=2007-05-10", "OVXCLS")
# P.remove_dots(2, "OVXCLS")
P.d_yfi(2, "QQQ")
P.percentages(2, "close")
# print(P.datasets[1]["subsets"])
# P.stacked(2, "close")
# P.inverse(2, "close")
# P.add(2, "close", 0.02)
# P.d_yfi(3, "NDQ.AX")
P.minimize([1, 2], normalize=True)
# our "callables" for date parsing our datasets
def fred(input):
return parse("year-month-day", str(input.split(" ")[0]), normalize=True)
def yahoofin_dp(input):
from packer import Packer
from fdates import parse
P = Packer()
P.d_csv(
1,
url="https://fred.stlouisfed.org/graph/fredgraph.csv?bgcolor=%23e1e9f0&chart_type=line&drp=0&fo=open%20sans&graph_bgcolor=%23ffffff&height=450&mode=fred&recession_bars=on&txtcolor=%23444444&ts=12&tts=12&width=1168&nt=0&thu=0&trc=0&show_legend=yes&show_axis_titles=yes&show_tooltip=yes&id=UNRATE&scale=left&cosd=1948-01-01&coed=2020-09-01&line_color=%234572a7&link_values=false&line_style=solid&mark_type=none&mw=3&lw=2&ost=-99999&oet=99999&mma=0&fml=a&fq=Monthly&fam=avg&fgst=lin&fgsnd=2020-02-01&line_index=1&transformation=lin&vintage_date=2020-10-29&revision_date=2020-10-29&nd=1948-01-01",
index="DATE",
subset="UNRATE",
name="number:Unemployment"
)
P.percentages(1, "UNRATE")
P.stacked(1, "UNRATE", inverse=True)
P.d_csv(
2,
url="https://fred.stlouisfed.org/graph/fredgraph.csv?bgcolor=%23e1e9f0&chart_type=line&drp=0&fo=open%20sans&graph_bgcolor=%23ffffff&height=450&mode=fred&recession_bars=on&txtcolor=%23444444&ts=12&tts=12&width=1168&nt=0&thu=0&trc=0&show_legend=yes&show_axis_titles=yes&show_tooltip=yes&id=INDPRO&scale=left&cosd=1919-01-01&coed=2020-09-01&line_color=%234572a7&link_values=false&line_style=solid&mark_type=none&mw=3&lw=2&ost=-99999&oet=99999&mma=0&fml=a&fq=Monthly&fam=avg&fgst=lin&fgsnd=2020-02-01&line_index=1&transformation=lin&vintage_date=2020-10-29&revision_date=2020-10-29&nd=1919-01-01",
index="DATE",
subset="INDPRO",
name="number:Industrial Production"
)
P.percentages(2, "INDPRO")
P.stacked(2, "INDPRO", inverse=True)
# P.d_csv(
# 3,
# url="https://fred.stlouisfed.org/graph/fredgraph.csv?bgcolor=%23e1e9f0&chart_type=line&drp=0&fo=open%20sans&graph_bgcolor=%23ffffff&height=450&mode=fred&recession_bars=on&txtcolor=%23444444&ts=12&tts=12&width=1168&nt=0&thu=0&trc=0&show_legend=yes&show_axis_titles=yes&show_tooltip=yes&id=BAMLH0A0HYM2&scale=left&cosd=2015-10-28&coed=2020-10-28&line_color=%234572a7&link_values=false&line_style=solid&mark_type=none&mw=3&lw=2&ost=-99999&oet=99999&mma=0&fml=a&fq=Daily%2C%20Close&fam=avg&fgst=lin&fgsnd=2020-02-01&line_index=1&transformation=lin&vintage_date=2020-10-29&revision_date=2020-10-29&nd=1996-12-31",
# index="DATE",
# subset="BAMLH0A0HYM2",
# name="number:Option Spreads"
from packer import Packer
from fdates import parse
P = Packer()
P.d_fred(
1,
"https://fred.stlouisfed.org/graph/fredgraph.csv?bgcolor=%23e1e9f0&chart_type=line&drp=0&fo=open%20sans&graph_bgcolor=%23ffffff&height=450&mode=fred&recession_bars=on&txtcolor=%23444444&ts=12&tts=12&width=1168&nt=0&thu=0&trc=0&show_legend=yes&show_axis_titles=yes&show_tooltip=yes&id=RRSFS&scale=left&cosd=1992-01-01&coed=2020-09-01&line_color=%234572a7&link_values=false&line_style=solid&mark_type=none&mw=3&lw=2&ost=-99999&oet=99999&mma=0&fml=a&fq=Monthly&fam=avg&fgst=lin&fgsnd=2020-02-01&line_index=1&transformation=lin&vintage_date=2020-10-29&revision_date=2020-10-29&nd=1992-01-01",
"RRSFS")
P.percentages(1, "RRSFS")
P.multiply(1, "RRSFS", 100)
P.stacked(1, "RRSFS")
# P.d_yfi(2, "^VIX")
# P.percentages(2, "close")
# P.inverse(2, "close")
# P.add(2, "close", 0.02)
P.minimize([1], normalize=True)
# our "callables" for date parsing our datasets
def nyfed_dp(input):
s = str(input).split(":")[0].split("T")[0]
return parse("year-month-day", s, normalize=True)
def yahoofin_dp(input):
return parse("year-month-day", str(input), normalize=True)