**Yes, the data has a geographic dimension. It is the `Location` column (the headquarters city of each funded startup), present in all five monthly tables, January to May 2022. Funding rounds are heavily concentrated in a few Indian metros.** The shares below are out of 446 rows in total (step-1 query). **Concentration** - **Bangalore** is the largest location with 124 rows (27.8%). - **Mumbai** has 62 rows (13.9%) and **Gurgaon** has 48 (10.8%). - **New Delhi** has 31 rows (7.0%) and **Chennai** has 27 (6.1%). - Together these five locations account for 292 of the 446 rows, about 65%. - **Noida** (15), **Hyderabad** (14) and **Pune** (12) follow, then a long tail of smaller cities. **Spelling variants split the counts** - Bangalore appears under three spellings: "Bangalore" (124), "Bengaluru" (10) and "Banglore" (6). Combined that is 140 rows, about 31%. - "New Delhi" (31) and "New delhi" (2) are also split, giving 33 rows combined. - Treating the spellings as separate places understates the lead of Bangalore and New Delhi. **Tail and gaps** - A small foreign presence appears: San Francisco (6), Delaware (3), Newyork (3), London (2) and Tokyo (2). - Some entries are states or regions rather than cities, for example Haryana (5), which makes the level of detail uneven. - 20 rows (4.5%) have a blank location. The dataset card notes that some May 2022 rows are misaligned or blank, which probably explains much of this. - The query lists only locations with at least 2 rows. Adding up the listed counts leaves about 32 rows spread across single-occurrence locations. This is my arithmetic from the listed counts, not a separate query. **Caveats** - Location is a free-text city name, not coordinates or a standardised geography. Any city or state comparison needs the spellings cleaned first. - The spelling variants and the 20 blank values affect the exact ranks and percentages, though not the overall picture.