Skip to main content

Parse data with no class

I have a code in python

from bs4 import BeautifulSoup
import requests
data0 = []
data1 = []
response = requests.get(
    "https://www.comicshoplocator.com/StoreLocatorPremier?query=75077&showCsls=true"
)
soup = BeautifulSoup(response.text, "html.parser")
for tag in soup.find_all('div', class_="LocationName"):
    title = tag.text
    data0.append({
        'title': title
    })

for button in soup.find_all('div', class_="LocationDetails"):
for childdiv in button.find_all('div', class_="LocationShopProfile"):
    for zb in childdiv.find_all('a'):
        if zb.get_text() == 'Shop Profile':
            website = zb.get('href')
            forsite = requests.get('https://www.comicshoplocator.com/' + website)
            soup = BeautifulSoup(forsite.text, "html.parser")
            for tag in soup.find_all('div', class_="StoreWeb"):
                site = tag.text.replace('Web: http://', '')
                data7.append({
                    'site': site
                })
df = pd.DataFrame(columns=['Name', 'Website'])

df[df.columns[0]] = pd.DataFrame(data0)
df[df.columns[1]] = pd.DataFrame(data1)

My print is:

                        Name                         Website
0       TWENTY ELEVEN COMICS      WWW.TWENTYELEVENCOMICS.COM
1                READ COMICS         www.boomerangcomics.com
2           BOOMERANG COMICS  www.facebook.com/morefuncomics
3  MORE FUN COMICS AND GAMES   www.madnesscomicsandgames.com
4     MADNESS COMICS & GAMES                             NaN
5  SANCTUARY BOOKS AND GAMES                             NaN

Correct print should be:

                        Name                         Website
0       TWENTY ELEVEN COMICS      WWW.TWENTYELEVENCOMICS.COM
1                READ COMICS                             NaN
2           BOOMERANG COMICS         www.boomerangcomics.com
3  MORE FUN COMICS AND GAMES  www.facebook.com/morefuncomics
4     MADNESS COMICS & GAMES   www.madnesscomicsandgames.com
5  SANCTUARY BOOKS AND GAMES                             NaN

Some stores may not have a "LocationShopProfile" or "StoreWeb" class. That is why second column have a wrong order

How can I fix that?

Thanks



source https://stackoverflow.com/questions/72999097/parse-data-with-no-class

Labels

Labels:

Comments

Post a Comment

Popular posts from this blog

How to split a rinex file if I need 24 hours data

Trying to divide rinex file using the command gfzrnx but getting this error. While doing that getting this error msg 'gfzrnx' is not recognized as an internal or external command Trying to split rinex file using the command gfzrnx. also install'gfzrnx'. my doubt is I need to run this program in 'gfzrnx' or in 'cmdprompt'. I am expecting a rinex file with 24 hrs or 1 day data.I Have 48 hrs data in RINEX format. Please help me to solve this issue. source https://stackoverflow.com/questions/75385367/how-to-split-a-rinex-file-if-i-need-24-hours-data
Post a Comment
Read more

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...
Post a Comment
Read more

Sorting large arrays of big numeric stings

I was solving bigSorting() problem from hackerrank: Consider an array of numeric strings where each string is a positive number with anywhere from to digits. Sort the array's elements in non-decreasing, or ascending order of their integer values and return the sorted array. I know it works as follows: def bigSorting(unsorted): return sorted(unsorted, key=int) But I didnt guess this approach earlier. Initially I tried below: def bigSorting(unsorted): int_unsorted = [int(i) for i in unsorted] int_sorted = sorted(int_unsorted) return [str(i) for i in int_sorted] However, for some of the test cases, it was showing time limit exceeded. Why is it so? PS: I dont know exactly what those test cases were as hacker rank does not reveal all test cases. source https://stackoverflow.com/questions/73007397/sorting-large-arrays-of-big-numeric-stings
Post a Comment
Read more