duncangh

"""
Investing Quick Analytics
Author: Elijah Lopez
Version: 1.49
Created: April 3rd 2020
Updated: March 16th 2021
https://gist.github.com/elibroftw/2c374e9f58229d7cea1c14c6c4194d27

Resources:
Black-Scholes variables:

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Developer blogs I've found and like

Individual run websites, so will exclude examples like "Netflix Engineering Blog" etc

• todo: export chrome bookmarks and make the links pretty with markdown
• todo: get more than one so this doesn't look like another abandoned project in my gist graveyard

https://www.craigkerstiens.com/ https://simonwillison.net/

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import requests
import pandas as pd
import plotly.graph_objects as go

import pandas as pd
from datetime import datetime

api_key = 'your api key from financialmodelingprep'

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{ "path": "/content/geometrixx/my-first-jinja-page",
  "properties": [
    { "name": "jcr:primaryType",
      "value": "cq:Page" }],
    
  "nodes": [
    { "path": "jcr:content",
      "properties": [
        { "name": "jcr:primaryType",
          "value": "cq:PageContent"},

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Summary

JupyterLab and Jupyter Notebook can display HTML-embedded images in notebook documents. You can use the IPython.display.HTML class to structure these images into a basic image gallery.

Example

The notebook below defines a gallery() function that accepts a list of image URLs, local image

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import random

import pandas as pd
import numpy as np
# import requests
# from bs4 import BeautifulSoup as bs

# base_setlist_url = "https://allthings.umphreys.com/setlists/2020.html"

df= pd.read_csv('https://gist.githubusercontent.com/duncangh/f732e79528c809c6affcfcbfaa087cba/raw/393a5861d749b0f1b60879038ce70eca99fe3517/songs.csv')

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• Pre Sum (hash map)

  • 1. Two Sum
  • 15. 3Sum
  • 18. 4Sum
  • 410. Split Array Largest Sum
  • 560. Subarray Sum Equals K

• Calculation

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// scroll to bottom
function autoScrolling() {
   window.scrollTo(0,document.body.scrollHeight);
}
var refreshIntervalId = setInterval(autoScrolling, 5); 
// run to cancel
clearInterval(refreshIntervalId);

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from lxml import html
import requests
import unicodecsv as csv
import argparse
import json


def clean(text):
    if text:
        return ' '.join(' '.join(text).split())