PHPMem v2.0.1

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1.6.45
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17 days 7 hours 56 minutes 54 seconds

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512MB
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12,72MB (2.48%)
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499,28MB

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14 060
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40 994
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llm:1e2d8d9be73b58cd0989f03dd83b29a139456d70d7a78af06e6b27c6d5364446
TTL 5 days 19 hours 28 minutes 11 seconds Size 2,82KB Export
Edit
Yes. The most natural grouping is **funding stage**, with **location** and **sector** as secondary cuts and **announcement month** as the time dimension. All of these need cleaning first. **1. Funding stage (the primary segmentation)** - Stage is the clearest classifier. The most common values are Seed (73), Series A (56), Pre-series A (37), Series B (26), Series C (19), Series D (14), Series F (12) and Series E (11). - It collapses into a maturity ladder: early (pre-seed, seed, angel), Series A/B, and growth (Series C and beyond), with "undisclosed" kept as its own segment. - Stage needs cleaning: - There are 127 blank stages, which is about 28% of the 446 rows. This is the largest single group, so treat it as its own "unknown" segment rather than dropping it. - "undisclosed" (37), "Undiclosed" (1) and "Unknown" (2) mean the same thing. - "Preseed" (2) should merge with "Pre-seed" (8). - "$Series A" (1) should merge with "Series A" and "Series-D" (1) with "Series D". - One stage value is actually investor names ("Blue Ashva Capital, Supack Industries"), and another is "Working Capital to SMEs". Both are misaligned or misplaced values. **2. Location (geography)** - Funding is concentrated in a few cities: Bangalore (124), Mumbai (62), Gurgaon (48), New Delhi (31), Chennai (27), Noida (15), Hyderabad (14) and Pune (12). - "Bangalore" and "Bengaluru" (10) are the same city and should be merged. Another 20 rows have a blank location. - A sensible grouping is the top metro hubs against everything else. **3. Sector (industry)** - Financial Services is the largest sector (59), followed by IT & Services (27), Computer Software (26), Health/Wellness/Fitness (15), E-learning (12), E-commerce (12) and Food & Beverages (11). - Sector has many distinct values, roughly 40 to 55 per monthly table, and inconsistent labels. "Financial Services" (59) and "Financial services" (13) are the same sector, and "Computer Software" and "Software" overlap. - It would work better rolled up into broader themes such as fintech, software/IT, health, and consumer/commerce. 19 rows have a blank sector. **4. Time (announcement month)** - The data is split across five tables, January to May 2022, with 115, 96, 98, 95 and 42 rows. Each table is effectively a month cohort. May is smaller and has misaligned or blank rows, so comparisons involving it are less reliable. **Recommendation:** after standardising labels, use stage (grouped into early, Series A/B, growth and unknown) as the main segment. Cross it with city hub and sector theme, and with month if you want a trend. The Amount column is stored as text, so it would need cleaning before you could add funding size as a segmentation or ranking measure. I did not analyse it here.