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Some of the companies provided in this dataset may be delisted or may not be available to download. url=" " s = requests.get(url).content companies = pd.read_csv(io.StringIO(s.decode('utf-8')))
#How to download stock quotes into excel code
The code below would access the URL containing a CSV file with the company names and their stock symbol, and convert it to a pandas dataframe. But the idea here is to look beyond the popular companies and unearth some interesting price movements for the not-so-well-known companies. The spreadsheet was designed in Excel for Windows but should also work in Excel for Mac. I have tried changing the ify file to the following, but it also didnt solve the problem. You then click the button, and the data is imported in your spreadsheet. When I open the link in a browser all is fine, however I cant link the data to my excel file. You can skip this step if you know exactly the companies you want the historical stock prices for (example: Tesla -> TSLA, Facebook -> FB etc). When you open the spreadsheet you will see options to select the market, date range and frequency (period). We want to get the stock ticker symbols listed on NASDAQ. start = datetime.datetime(2020,2,1) end = datetime.datetime(2020,10,11) Step 3: Get the Stock Ticker Symbols You could set the start and end date to anything you like- but what I am trying to analyze is the price fluctuation from pre-pandemic times till now. Below, I have provided the start date as 1st February 2020 (approximate beginning of this year’s misery) and end date as 11th October 2020, the current date when I executed this code. Next, we want to provide the start and end dates, during which period we want the daily stock prices. import pandas as pd import yfinance as yf import datetime import time import requests import io Step 2: Set the date range
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What we need is pandas (the bread and butter for data science in python), yfinance for downloading the historical stock prices from yahoo finance, datetime and time which provides functions to manipulate dates and times, requests for sending HTTP requests and io for handling strings. Open up a notebook and follow along: Step 1: Download the required packages.
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