Ausgabe als Liste drucken

Question

Der folgende Code läuft einwandfrei. Es sammelt Informationen pro Eintrag auf LinkedIn.

(Kontoinformationen angegeben und kostenlos zu verwenden, da es sich um ein Testkonto handelt)

Die Ausgabe verbindet jedoch die Daten, anstatt dass jedes Feld ein eigenes Feld hat.

Ich möchte, dass die Ausgabe in Excel mit jedem Feld im Wörterbuch (Name, Firma, Standort) in einer eigenen Spalte gedruckt wird, wobei sich die Ausgaben in einer eigenen Zelle befinden.

Im Anhang finden Sie ein Beispiel für die erwartete Ausgabe.

Ich habe beautifulSoup ausprobiert, glaube aber nicht, dass das funktioniert.

import time
import pandas as pd
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('[email protected]')
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)

Answer 1

Ich kann Ihren Code ausführen,

Folgendes erhalte ich mithilfe von Efficient Way, um mehrere Listenspalten in einem Pandas DataFrame zu entfernen (zu explodieren)

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('[email protected]')
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)

def explode(df, lst_cols, fill_value=''):
    # make sure `lst_cols` is a list
    if lst_cols and not isinstance(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 empty
        return 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 empty
        return 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'])

Und das Ergebnis

    Location            Company                                 Title
0   Dayton, Ohio Area   National Account Executive              LinkedIn Member
1   Dayton, Ohio Area   Currently seeking permanent employment  LinkedIn Member
2   Dayton, Ohio Area   Account Manager at LexisNexis           LinkedIn Member
3   Greater Denver Area Currently seeking new opportunities in managem...   LinkedIn Member
4   Dayton, Ohio Area   Advertising Sales Representative at AMOS MEDIA  LinkedIn Member
5   Dayton, Ohio Area   Territory Manager at Huntington Outdoor, LLC    LinkedIn Member
6   Vandalia, Ohio, United States   Cintas  LinkedIn Member
7   Dayton, Ohio Area   Outside Sales Representative at Carter Lumber.  LinkedIn Member
8   Dayton, Ohio Area   Actively Searching  LinkedIn Member
9   Corpus Christi, Texas Area  Currently looking for sales position    LinkedIn Member