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import streamlit as st
import pandas as pd
import numpy as np
from apify_client import ApifyClient
import requests
# Function to fetch Google Maps info
def fetch_google_maps_info(website_name):
apify_client = ApifyClient("apify_api_uz0y556N4IG2aLcESj67kmnGSUpHF12XAkLp")
run_input = {"searchStringsArray": [website_name]}
run = apify_client.actor("nwua9Gu5YrADL7ZDj").call(run_input=run_input)
items = list(apify_client.dataset(run["defaultDatasetId"]).iterate_items())
return items[0] if items else None
# Function to fetch website content using Apify actor
def fetch_website_content(website_url):
apify_client = ApifyClient("apify_api_uz0y556N4IG2aLcESj67kmnGSUpHF12XAkLp")
run_input = {"startUrls": [website_url]}
run = apify_client.actor("moJRLRc85AitArpNN").call(run_input=run_input)
items = list(apify_client.dataset(run["defaultDatasetId"]).iterate_items())
return items[0] if items else None
# Function to fetch weather info
def fetch_weather_info(lat, lon):
API_KEY = "91b23cab82ee530b2052c8757e343b0d"
url = f"https://api.openweathermap.org/data/3.0/onecall?lat={lat}&lon={lon}&exclude=hourly,daily&appid={API_KEY}"
response = requests.get(url)
return response.json()
# Streamlit app
st.title("Data Visualization")
website_name = st.text_input("Enter a website / company name:")
if website_name:
google_maps_data = fetch_google_maps_info(website_name)
if google_maps_data:
# Display website link in a specific output box
website_link = google_maps_data.get('website')
st.text_area("Website Link:", website_link)
# Fetch and display website content
website_content = fetch_website_content(website_link)
if website_content:
st.subheader("Scraped Website Content")
content_df = pd.DataFrame(website_content)
st.table(content_df)
# Display location and fetch weather info
lat = google_maps_data["location"]["lat"]
lng = google_maps_data["location"]["lng"]
if lat and lng:
st.map(pd.DataFrame({'lat': [lat], 'lon': [lng]})) # Display the map
weather_data = fetch_weather_info(lat, lng)
current_weather = weather_data.get("current", {})
temp_in_celsius = current_weather.get('temp') - 273.15
st.write(f"**Location:** {lat}, {lng}")
st.write(f"**Temperature:** {temp_in_celsius:.2f}°C")
st.write(f"**Weather:** {current_weather.get('weather')[0].get('description')}")
# Occupancy Data
st.subheader("Occupancy Data")
occupancy_data = google_maps_data.get('popularTimesHistogram', {})
for day, day_data in occupancy_data.items():
if day_data:
hours = [entry['hour'] for entry in day_data]
occupancy = [entry['occupancyPercent'] for entry in day_data]
st.write(day)
st.bar_chart(pd.Series(occupancy, index=hours), use_container_width=True)
# Review Count and Distribution
st.subheader("Review Count and Distribution")
st.write(f"Total Reviews Count: {google_maps_data['reviewsCount']}")
review_distribution = google_maps_data['reviewsDistribution']
days_order = ['Mo', 'Tu', 'We', 'Th', 'Fr', 'Sa', 'Su']
ordered_distribution = {day: review_distribution.get(day, 0) for day in days_order}
st.bar_chart(pd.Series(ordered_distribution), use_container_width=True)
# Reviews Table
st.subheader("Customer Reviews")
reviews = google_maps_data.get('reviews', [])
if reviews:
review_df = pd.DataFrame(reviews)
st.table(review_df[['name', 'text', 'publishAt', 'likesCount', 'stars']])
else:
st.write("No reviews available.")
else:
st.write("No results found for this website / company name on Google Maps.") |