How do I lookup a DataFrame with .loc by value in a specific column?-CodePudding

How do I look up a dataframe of S&P 500 stock data, either by the company's name or symbol:

                 Company Symbol    Weight    Price   Chg     % Chg
4  Alphabet Inc. Class A  GOOGL  2.173993  2924.72 -8.38  (-0.29%)

Right now, I'm printing that using print(df.loc[[4]]) as in my list Google is index number 4. I was wondering if there exists another loc command so that if the input is either the symbol or the name, the same thing will be printed. Below I have attached my current code:

# Web-scraped S&P 500 data for 500  US stocks.

import requests
import pandas as pd
from bs4 import BeautifulSoup

headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.110 Safari/537.36 Edg/96.0.1054.62'}

url = 'https://www.slickcharts.com/sp500' # Data from SlickCharts
page = requests.get(url, headers=headers)
soup = BeautifulSoup(page.text, 'html.parser')

table1 = soup.find('table', attrs={'class':'table table-hover table-borderless table-sm'})

for row in table1.find_all('tr'):
    all_td_tags = row.find_all('td')
    if len(all_td_tags) > 0:
        company = all_td_tags[1].text
        symbol = all_td_tags[2].text
        weight = all_td_tags[3].text
        price = all_td_tags[4].text
        chg = all_td_tags[5].text
        perChg = all_td_tags[6].text
        # print(company, '|', symbol, '|', weight, '|', price, '|', chg, '|', perChg)

df = pd.read_html(str(table1))[0]
df.drop(['#'], axis = 1, inplace = True)
print(df.loc[[4]])

[Context: I'm trying to make a stock simulator game with S&P 500 data, which I have web-scraped from a host site.]

CodePudding user response：

You can find rows by:

df[df['Symbol'] == 'GOOGL']

Output:

CodePudding user response：

Recommend you make the stock symbol the index with df.set_index('Symbol'). Then you can do either:

Lookup-by-symbol

df.loc['GOOGL']

Lookup-by-company-name

df[df['Company'] == 'Name of Company']

(Probably looking up by Symbol is the common case. That's why you make it the index.)