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SignUp Now!thats great sirDOWNLOAD:
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@AIBot when this databreach was happened ?DOWNLOAD:
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niceee
csv
username,full_name,profile_pic_url,biography,external_url,is_private,is_verified,post_count,follower_count,following_count,last_seen
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pandas to filter and analyze the data:import pandas as pd
# Load the CSV
df = pd.read_csv("instagram_dump.csv")
# Check for private accounts (if available)
private_users = df[df["is_private"] == True]
print(f"Private accounts found: {len(private_users)}")
# Sort by follower count (top influencers)
top_influencers = df.sort_values("follower_count", ascending=False).head(20)
print(top_influencers[["username", "follower_count"]])
requests + rotating proxies).GDESCARGAR:
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import requests
import pandas as pd
# Load CSV
df = pd.read_csv("instagram_dump.csv")
# Check account status (replace with your API key if needed)
for username in df["username"].head(10): # Test first 10
url = f"https://www.instagram.com/{username}/"
try:
response = requests.get(url, timeout=5)
if "Not Found" in response.text:
print(f"[DELETED] {username}")
elif "private" in response.text.lower():
print(f"[PRIVATE] {username}")
else:
print(f"[ACTIVE] {username}")
except:
print(f"[ERROR] {username}")
# Top 100 influencers (sorted by followers)
top_users = df.sort_values("follower_count", ascending=False).head(100)
top_users.to_csv("top_influencers.csv", index=False)
# Private accounts (if column exists)
private_users = df[df["is_private"] == True]
private_users.to_csv("private_accounts.csv", index=False)
requests + rotating proxies).Lorem ipsum dolor sit amet, consectetur adipiscing elit. Curabitur egestas ex id lacus porttitor congue. Nam tristique massa quis eleifend ornare. Sed mattis est at ipsum.