How to solve issue exporting DataFrame to CSV? - pandas

Question

I am extracting some text (HTML) from a txt file. There are about 9 rows that need to extracted and slpit the data up into 4 columns (Field_01 to Field_04) which seems to works well in the VS terminal. However, when I export the data to a csv, 2 issues arise. The first is that the data that should be in the 2nd column is split between the 2nd 3rd and 4th column, while the data that should be in the 3rd and 4th column are pushed to a 5th and 6th. The second issues is that, in the terminal I get all 9 rows, but only one row is exported to the CSV file.
Here is my code...
import pandas as pd
from bs4 import BeautifulSoup
import schedule
import time
#import urllib.parse
#import requests
baseurl = 'https://hippeas.com'
data = open("/run/user/759001103/gvfs/smb-share:server=192.168.0.150,share=indexserver/code.txt", "r")
info = data.readlines()
#print(info)
for items in info:
if items.startswith(" <img src="):
reduce_imgurl = items.split('//')[-1]
if items.startswith(" <h3 class="):
reduce_name = items[39:-6]
if items.startswith(" <a href="):
reduce_link = items[11:-32]
if items.startswith(" <span class="):
reduce_price = items[55:-8]
#print(reduce_imgurl, reduce_name, baseurl + reduce_link, reduce_price)
dataset = {'Field_01':[reduce_imgurl],'Field_02':[reduce_name],'Field_03':[baseurl + reduce_link],'Field_04':[reduce_price]}
#print(dataset)
df = pd.DataFrame(dataset, columns=('Field_01','Field_02','Field_03','Field_04'))
print(df)
df.to_csv(r'/run/user/759001103/gvfs/smb-share:server=192.168.0.150,share=indexserver/Testcode.csv', index = False)
Here is what it shows in the terminal vs the results...
Terminal and csv result

Answer 1

The question should only focus on one issue, so this answer only refers to the actual issue. Furthermore, the content should be parsed with BeautifulSoup if it is HTML, but this is not used at all despite tagging.
The problem is that the CSV is overwritten over and over again in the for-loop. One solution would be to decouple the extracting part from the writing part:
...
dataset = []
for items in info:
if items.startswith(" <img src="):
reduce_imgurl = items.split('//')[-1]
if items.startswith(" <h3 class="):
reduce_name = items[39:-6]
if items.startswith(" <a href="):
reduce_link = items[11:-32]
if items.startswith(" <span class="):
reduce_price = items[55:-8]
dataset.append({'Field_01':reduce_imgurl,'Field_02':reduce_name,'Field_03':baseurl + reduce_link,'Field_04':reduce_price})
pd.DataFrame(dataset).to_csv(r'PATH_TO_FILE', index = False)