Yes, the dataset has a geographic dimension (the `Location` column, present in all five monthly tables). Funding rounds are heavily concentrated in a few Indian metros. The figures come from the location breakdown across all 446 rows, shown in the rendered table. - **Bangalore leads by a wide margin.** It has 124 rows (27.8%), about twice the next city, Mumbai (62 rows, 13.9%). - **Three cities make up over half the data.** Bangalore, Mumbai and Gurgaon (48 rows, 10.8%) together account for about 52% of all rows. Adding New Delhi (31, 7.0%) and Chennai (27, 6.1%) brings the top five to roughly 66%. - **Smaller hubs follow.** These are Noida (15), Hyderabad (14), Pune (12), Jaipur (6) and Ahmedabad (5). Delhi-NCR is also spread across Gurgaon, New Delhi, Noida and Faridabad. - **A few locations are outside India.** San Francisco (6), Newyork (3), Delaware (3) and Tokyo (2) appear, probably startups with foreign headquarters. **Data quality caveats:** - **Bangalore is split across spellings.** "Bangalore" (124), "Bengaluru" (10) and "Banglore" (6) are the same city. Combined they total 140 rows, about 31.4%, so Bangalore's dominance is understated. - **Some locations are blank.** 20 rows (4.5%) have no location. The card notes that some May 2022 rows are misaligned or blank, which likely explains part of this. - **Some values are states, not cities.** "Haryana" (5 rows) is a state, so the column mixes granularities. - **The long tail is truncated.** The breakdown lists the top 20 values, so smaller locations beyond these are not shown. For any city-level analysis, standardise the Bangalore spellings and handle the blank locations first.