Yes. The `City Location` column gives the data a geographic dimension, and deals are heavily concentrated in a few metros. **Raw values (step 0 and step 1).** The column is messy: "Bangalore" and "Bengaluru" are separate labels, as are "Gurgaon" and "Gurugram", and "New Delhi" and "Delhi". Some values carry hidden non-breaking-space prefixes (`\xa0Gurgaon`, `\xa0New Delhi`). There are also compound entries such as "Pune / US". **After merging the obvious spelling variants (step 2).** The 3,044 deals break down like this: - **Bengaluru:** 841 deals (27.6%), the largest hub. It is the sum of "Bangalore" (700) and "Bengaluru" (141). - **Mumbai:** 567 deals (18.6%). - **Delhi / New Delhi:** 455 deals (14.9%). - **Gurugram:** 337 deals (11.1%). - **Mid-sized cities:** Pune (105), Hyderabad (99), Chennai (97) and Noida (92) each hold about 3%. - **Long tail:** Ahmedabad (38), Jaipur (30), Kolkata (21), Indore (13), Chandigarh (11), Goa (10), Vadodara (10), Singapore (8), Coimbatore (5) and Kanpur (4). **Key takeaways** - Four locations (Bengaluru, Mumbai, Delhi and Gurugram) account for about 72% of deals. - Delhi, Gurugram and Noida together make up the National Capital Region (NCR). Combined, they are about 884 deals, roughly 29% of the total and larger than Mumbai alone. That figure comes from adding the step 2 counts, not from a separate query. - Everything beyond the top nine cities is a long tail of small counts, each at or below about 1%. - A few deals are outside India, such as Singapore (8) and the "Pune / US" entries. **Data quality caveat.** About 5.6% of rows (171) have the literal text "nan" as the city. A further 6 are blank and 3 are "N/A", so roughly 6% of deals have no usable location. The consolidated percentages treat these as their own bucket, and a few `\xa0`-prefixed variants (such as `\xa0Gurgaon`) fall in the small remainder. The rendered result tables above show the full counts. Any city-level analysis should clean the column first, by trimming whitespace and merging the spelling variants.