Timeseries

# Daily metrics (default)
curl -X GET "https://attractos.com/api/v1/sites/site_abc123/timeseries?start=2024-01-01&end=2024-01-31" \
  -H "Authorization: Bearer YOUR_API_KEY"

# Hourly metrics (Pro only)
curl -X GET "https://attractos.com/api/v1/sites/site_abc123/timeseries?start=2024-01-15&end=2024-01-15&granularity=hour" \
  -H "Authorization: Bearer YOUR_API_KEY"

const siteId = 'site_abc123';
const params = new URLSearchParams();
params.set('start', '2024-01-01');
params.set('end', '2024-01-31');
params.set('granularity', 'day');

const url = 'https://attractos.com/api/v1/sites/' + siteId + '/timeseries?' + params;
const response = await fetch(url, {
  headers: { 'Authorization': 'Bearer YOUR_API_KEY' },
});

const data = await response.json();

// Format for charting library
const chartData = data.data.map(function(point) {
  return {
    date: new Date(point.date),
    bots: point.bot_visits,
    referrals: point.referrals,
    conversions: point.conversions,
  };
});

import requests
import pandas as pd

site_id = 'site_abc123'
response = requests.get(
    f'https://attractos.com/api/v1/sites/{site_id}/timeseries',
    headers={'Authorization': 'Bearer YOUR_API_KEY'},
    params={
        'start': '2024-01-01',
        'end': '2024-01-31',
        'granularity': 'day',
    }
)

data = response.json()

# Create DataFrame for analysis
df = pd.DataFrame(data['data'])
df['date'] = pd.to_datetime(df['date'])
df.set_index('date', inplace=True)

print(df.describe())