new_obs.append(zl.get_bedrooms(card_info))
# Bathrooms
new_obs.append(zl.get_bathrooms(card_info))
# Days on the Market/Zillow
new_obs.append(zl.get_days_on_market(soup))
# Sale Type (House for Sale, New Construction, Foreclosure, etc.)
new_obs.append(zl.get_sale_type(soup))
# URL for each house listing
new_obs.append(zl.get_url(soup))
# Append new_obs to list output_data.
output_data.append(new_obs)
# Close the webdriver connection.
zl.close_connection(driver)
# Write data to data frame, then to CSV file.
file_name = "%s_%s.csv" % (str(
time.strftime("%Y-%m-%d")), str(time.strftime("%H%M%S")))
columns = [
"address", "city", "state", "zip", "price", "sqft", "bedrooms",
"bathrooms", "days_on_zillow", "sale_type", "url"
]
pd.DataFrame(output_data, columns=columns).to_csv(file_name,
index=False,
encoding="UTF-8")
# Bedrooms
new_obs.append(parser.get_bedrooms())
# Bathrooms
new_obs.append(parser.get_bathrooms())
# Days on the Market/Zillow
new_obs.append(parser.get_days_on_market())
# Sale Type (House for Sale, New Construction, Foreclosure, etc.)
new_obs.append(parser.get_sale_type())
# URL for each house listing
new_obs.append(parser.get_url())
# Append new_obs to list output_data.
output_data.append(new_obs)
# Close the webdriver connection.
zl.close_connection(driver)
# Write data to data frame, then to CSV file.
file_name = "%s_%s.csv" % (str(time.strftime("%Y-%m-%d")),
str(time.strftime("%H%M%S")))
columns = ["address", "city", "state", "zip", "price", "sqft", "bedrooms",
"bathrooms", "days_on_zillow", "sale_type", "url"]
pd.DataFrame(output_data, columns = columns).drop_duplicates().to_csv(
file_name, index = False, encoding = "UTF-8"
)