Print Output In As A List

The following code runs fine. It gathers information per listing on LinkedIn. (Account info given and free to use as it is a test account) However, the output joins the data instea

Solution 1:

I can run your code,

Here is what I get, with help from Efficient way to unnest (explode) multiple list columns in a pandas DataFrame

import time
import pandas as pd
import numpy as np
from selenium import webdriver
from bs4 import BeautifulSoup
import requests
from selenium.webdriver.chrome.options import Options
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from webdriver_manager.chrome import ChromeDriverManager
test1=[]
options = Options()
driver = webdriver.Chrome(ChromeDriverManager().install())

url = "https://www.linkedin.com/uas/login?session_redirect=https%3A%2F%2Fwww%2Elinkedin%2Ecom%2Fsearch%2Fresults%2Fpeople%2F%3FcurrentCompany%3D%255B%25221252860%2522%255D%26geoUrn%3D%255B%2522103644278%2522%255D%26keywords%3Dsales%26origin%3DFACETED_SEARCH%26page%3D2&fromSignIn=true&trk=cold_join_sign_in"
driver.get(url)
time.sleep(2)

username = driver.find_element_by_id('username')
username.send_keys('kbradons04@gmail.com')
password = driver.find_element_by_id('password')

password.send_keys('Applesauce1')
password.submit()
driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")

time.sleep(3)

elementj=(WebDriverWait(driver,10).until(EC.visibility_of_all_elements_located((By.CSS_SELECTOR,".subline-level-2.t-12.t-black--light.t-normal.search-result__truncate"))))
place1=[j.text for j in elementj]


elementk=WebDriverWait(driver,10).until(EC.visibility_of_all_elements_located((By.CSS_SELECTOR,".subline-level-1.t-14.t-black.t-normal.search-result__truncate")))
compan=[c.text for c in elementk]


element1 = driver.find_elements_by_class_name("actor-name")
title=[t.text for t in element1]


diction={"Location":place1,"Company":compan,"Title":title}
test1.append(diction)
print(test1)

df = pd.DataFrame(test1)

defexplode(df, lst_cols, fill_value=''):
    # make sure `lst_cols` is a listif lst_cols andnotisinstance(lst_cols, list):
        lst_cols = [lst_cols]
    # all columns except `lst_cols`
    idx_cols = df.columns.difference(lst_cols)

    # calculate lengths of lists
    lens = df[lst_cols[0]].str.len()

    if (lens > 0).all():
        # ALL lists in cells aren't emptyreturn pd.DataFrame({
            col:np.repeat(df[col].values, df[lst_cols[0]].str.len())
            for col in idx_cols
        }).assign(**{col:np.concatenate(df[col].values) for col in lst_cols}) \
          .loc[:, df.columns]
    else:
        # at least one list in cells is emptyreturn pd.DataFrame({
            col:np.repeat(df[col].values, df[lst_cols[0]].str.len())
            for col in idx_cols
        }).assign(**{col:np.concatenate(df[col].values) for col in lst_cols}) \
          .append(df.loc[lens==0, idx_cols]).fillna(fill_value) \
          .loc[:, df.columns]

explode(df,['Location','Company','Title'])

And the result

    Location            Company                                 Title
0   Dayton, Ohio Area   National Account Executive              LinkedIn Member1   Dayton, Ohio Area   Currently seeking permanent employment  LinkedIn Member2   Dayton, Ohio Area   Account Manager at LexisNexis           LinkedIn Member3   Greater Denver Area Currently seeking new opportunities in managem...   LinkedIn Member4   Dayton, Ohio Area   Advertising Sales Representative at AMOS MEDIA  LinkedIn Member5   Dayton, Ohio Area   Territory Manager at Huntington Outdoor, LLC    LinkedIn Member6   Vandalia, Ohio, United States   Cintas  LinkedIn Member7   Dayton, Ohio Area   Outside Sales Representative at Carter Lumber.  LinkedIn Member8   Dayton, Ohio Area   Actively Searching  LinkedIn Member9   Corpus Christi, Texas Area  Currently looking for sales position    LinkedIn Member