dharmatech

A-1d.pkl
AAPY-1d.pkl
AAT-1d.pkl
AB-1d.pkl
ABVE-1d.pkl
ACIO-1d.pkl
ACNB-1d.pkl
ACV-1d.pkl
ACVF-1d.pkl
ACWI-1d.pkl

dharmatech

ACRS-1d.pkl
ADCT-1d.pkl
ANIX-1d.pkl
AOMR-1d.pkl
APLD-1d.pkl
APLY-1d.pkl
ASRV-1d.pkl
AVO-1d.pkl
BAX-1d.pkl
BCOV-1d.pkl

dharmatech

import pandas as pd
import treasury_gov_pandas

import streamlit as st
import plotly
import plotly.express

# @st.cache_data
def get_dataframe():
    return treasury_gov_pandas.load_records('https://api.fiscaldata.treasury.gov/services/api/fiscal_service/v1/accounting/od/auctions_query', lookback=10, update=False)

dharmatech

import io
import requests
import pandas as pd

def trade_quote(symbol, expiration, date):

    url = "http://127.0.0.1:25510/v2/bulk_hist/option/trade_quote"
    
    querystring = { "root": symbol, "exp": expiration, "start_date": date, "end_date": date, "use_csv":"true" }

dharmatech

import pandas as pd
import treasury_gov_pandas.datasets.mts.mts_table_4.load
import streamlit as st
import plotly.express as px
import numpy as np

df = treasury_gov_pandas.datasets.mts.mts_table_4.load.load()

# convert null values to 0 in the column 'current_month_net_rcpt_amt'

dharmatech

import os
import glob
import pandas as pd

from bokeh.plotting import figure, show
from bokeh.models import ColumnDataSource, HoverTool
from bokeh.transform import linear_cmap
from bokeh.palettes import Viridis256
from bokeh.io import output_notebook

dharmatech

from bokeh.plotting import figure, show

import bokeh.models

import bokeh.palettes
import bokeh.transform

import pandas as pd

dharmatech

from bokeh.plotting import figure, show

import bokeh.models

import bokeh.palettes
import bokeh.transform

import pandas as pd

dharmatech

import pandas as pd
import treasury_gov_pandas
from bokeh.plotting import figure, show
from bokeh.models   import NumeralTickFormatter, HoverTool
import bokeh.models

import bokeh.palettes
import bokeh.transform
# ----------------------------------------------------------------------
df = treasury_gov_pandas.update_records(

dharmatech

import yfinance_download

from bokeh.plotting import figure, show
import bokeh.models
import bokeh.palettes
import bokeh.transform

df = yfinance_download.update_records('^GSPC', interval='1d')