debpu06

def q6():
    #Starting point
    eps = .000001 #specify the convergence criteria

    #Step 1: initial guess x0
    x0=0

    #Step 2: compute x1 by applying the function
    def BR(q): #this is our function of interest
        return 1+0.1*q

debpu06

from matplotlib.backends.backend_pdf import PdfPages
%matplotlib inline
def inverse_supply(quantity):
    '''Inverse supply function $p_s = {\sqrt{q_s} }$, where quantity is inputed and price is output'''
    return (math.sqrt(quantity))

def inverse_supply_with_tax(quantity):
    '''Inverse supply function with the tax added $p_s = {\sqrt{q_s} } + 2$, where quantity is inputed and price is output'''
    return inverse_supply(quantity) + 2

debpu06

import pandas as pd
import os

# Sample code to calculate the Beta coefficient; Assume we have the following 9 weeks prices for a stock and the market index
Stock_WeeklyPrice = [20,35,40,37,22,34,55,35,42]
Market_WeeklyPrice = [300, 340, 400, 320, 200, 300, 500, 380, 400]

def calculate_beta(stock_weekly_price, market_weekly_price):
    # A useful code to calculate the percentage change within a series is called np.Series.pct_change()
    # It returns the percentage change between the current and a prior element, which can be seen as (P_t / P_(t-1))-100%

debpu06

# Starting point
class State:
        def __init__(self, name, pop,s_intercept=0,d_intercept=100):
            self.name = name
            self.population = pop
            
            #supply function parameters
            self.supply_intercept=s_intercept
            self.supply_slope=1
        

debpu06

pp = PdfPages(outputfolder + 'my_pdf_name.pdf') # create a new instance of PdfPages specifying the file location
    
figs = [fig1, fig2, fig3] # all of the figures to add to the file in a list
    
for fig in figs: # loop through each figure
    fig.savefig(pp, format='pdf') # save that figure to the file, specifying pdf format
pp.close() # close the file

debpu06

import { SITE_OWNER_GITHUB, SITE_OWNER_LINKEDIN, SITE_OWNER_TWITTER, SITE_OWNER, SITE_URL } from '../../lib/constants'

export default function PostSchema({ post }) {

    const url = post.canonicalUrl !== undefined && post.canonicalUrl !== null ? post.canonicalUrl : `${SITE_URL}/blog/${post.slug}`;

    return (
      <script
                defer
                type="application/ld+json"

debpu06

import React from 'react'
import { BLOCKS, MARKS } from '@contentful/rich-text-types';
import { documentToReactComponents } from '@contentful/rich-text-react-renderer';
import { GatsbyImage, getImage } from "gatsby-plugin-image"

const Bold = ({ children }) => <b>{children}</b>;

const Text = ({ children }) => <p className="align-center">{children}</p>;

const richTextImages = {};

debpu06

import { graphql } from "gatsby"

export const TextQuery = graphql`
  fragment TextBlock on ContentfulTextBlock {
    id
    bodyContent {
      json
    }
    sys {
      contentType {

debpu06

import { graphql } from "gatsby"

export const FiftyFiftyContentQuery = graphql`
  fragment FiftyFiftyContent on ContentfulFiftyFifty {
    id
    sys {
      contentType {
        sys {
          id
        }

debpu06

/*
---
name: Image Gallery
category: Javascript
example: https://www.uspoloassnglobal.com/collections/Polo-Player-Inspired
description: Load the optimal image size for each tile: Get the clients screen resolution and multiply it by the dimensions of the tile. If client changes media query, then refresh these images.
---
```
*/