CODEWITHSUNDEEP
pythonpandasdataframe
Soumya Pandey
Soumya Pandey

Reputation: 331

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all() for a for loop

import requests
from bs4 import BeautifulSoup
import pandas as pd

header = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/87.0.4280.88 Safari/537.11',
       'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
       'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
       'Accept-Encoding': 'none',
       'Accept-Language': 'en-US,en;q=0.8',
       'Connection': 'keep-alive'}

def scrap_hrefs(url,baseUrl):
    resp = requests.get(url, headers= header)
    respData = BeautifulSoup(resp.content, 'html.parser')     
    allHrefs = respData.select('[href]')
    
    return allHrefs, baseUrl
   
def get_hrefs(allHrefs, baseUrl):
    for i in range(0,len(allHrefs)):
        if allHrefs[i]['href'].startswith('/'):
            allHrefs[i]= baseUrl + allHrefs[i]['href']
        else:
            allHrefs[i]= allHrefs[i]['href']
            
    return allHrefs

def store_hrefs(allHrefs):
    links = {'links' : allHrefs}
    df = pd.DataFrame(links).drop_duplicates()
    for i in range(len(df.index)):
        if df['links'].str.contains('https')==False:
            df.drop()        
    df.to_csv("example_home_page_links.csv", index=False)
    
    return df
    
def run_scraper(url,baseUrl) :
    store_hrefs(get_hrefs(*scrap_hrefs(url, baseUrl)))
     
    
run_scraper('https://www.example.com/','https://www.example.com')

this code is giving the following error :

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

I want to remove all the rows in which 'https' is not there(i.e. remove all the invalid links/content).

Upvotes: 1

Views: 851

Answers (1)

jezrael
jezrael

Reputation: 862761

You can change remove False output in loop:

for i in range(len(df.index)):
    if df['links'].str.contains('https')==False:
        df.drop()

to filter only rows with match condition in boolean indexing:

df = df[df['links'].str.contains('https')]

Upvotes: 2

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