Yes, every table has a `Location` column (a city or region of the startup), and the data is heavily concentrated in a few Indian metros. These figures are the location counts across all five monthly tables (446 rows) that I queried in step 2. **Concentration** - **Bangalore** is the largest location with 124 rows (27.8%). Counting spelling variants "Bengaluru" (10) and "Banglore" (6), it rises to about 140 rows (~31%). "Kormangala" (1 row) is also a Bangalore neighbourhood. - **Mumbai** has 62 rows (13.9%), plus one typo, "Mumba". - **Delhi NCR** is split across several labels: - Gurgaon 48 rows (10.8%) - New Delhi 31 (7.0%) - Noida 15 (3.4%) - Faridabad 3 - "New delhi" 2 Together these come to about 99 rows (~22%). I left out the 5 "Haryana" rows, which is a state rather than a city. - **Other cities:** Chennai (27, 6.1%), Hyderabad (14, 3.1%), Pune (12, 2.7%), then a long tail of 1–6 rows each, including Jaipur, Ahmedabad, Kolkata, Surat, Thane and Coimbatore. By these counts, Bangalore, Mumbai and Delhi NCR together account for roughly two-thirds of all funding rows. **International presence** A small number of rows sit outside India, about 4% in total: - San Francisco: 6 - Delaware: 3 - New York (spelled "Newyork"): 3 - Tokyo: 2 - London: 2 - Amsterdam: 1 - Maryland: 1 These are likely startups with a foreign base or a US-incorporated parent. **Data-quality caveats** - 20 rows (4.5%) have a blank location. The card notes that some May 2022 rows are misaligned or blank. - Spellings are inconsistent: Bangalore/Bengaluru/Banglore, New Delhi/New delhi, Mumbai/Mumba, Ahmedabad/Ahemdabad. - Granularity is mixed: some values are cities, some are states (Haryana, Delaware, Maryland), and one is a neighbourhood (Kormangala). - Without cleaning, the city shares above are understated for Bangalore and Delhi NCR. - The 30 locations in the result add up to roughly 419 of the 446 rows by my arithmetic. The remaining ~27 rows are in locations with a single row each that fell outside the listed result.