Eight of the nine business columns have missing values. Only `Company Name` has none in January–April; its 19 missing values are all in May. `Stage` is by far the worst, at about 28% missing. **How I counted "missing":** Counting only SQL NULLs gave 0% everywhere (step 2). Missing values in this data are stored as empty or bracketed-empty strings, such as a `Stage` of `[]` (step 3). The figures below count those blank values as missing (steps 4–6, 9). **Overall missing rate across all 446 rows (Jan–May 2022)**, computed from the ALL row of the step-9 counts: | Column | Missing rows | % missing | |---|---|---| | Stage | 127 | ~28.5% | | Investor | 45 | ~10.1% | | Founders | 38 | ~8.5% | | Amount | 25 | ~5.6% | | Location | 20 | ~4.5% | | Company Name | 19 | ~4.3% | | Sector | 19 | ~4.3% | | Founded | 18 | ~4.0% | | What it does | 18 | ~4.0% | **Where the gaps sit, by month:** - **Stage:** January has 43 of 115 rows missing (37.4%), February 29 (30.2%), March 31 (31.6%) and May 21 (50.0%). April has only 3 (3.2%). - **Investor:** January has 5 missing (4.3%), February 6 (6.3%), March 3 (3.1%), April 10 (10.5%) and May 21 (50.0%). - **Founders:** April has 10 missing (10.5%) and May has 27 (64.3%). February has 1 and January and March have none. - **Amount:** January, March, April and February have 0, 0, 2 and 2 missing respectively, and May has 21 (50.0%). - **Company Name, Founded, Location, Sector and What it does:** These are essentially complete in January–April, apart from 1 missing `Location` in April and 1 missing `Founders` in February. In May, about 43–45% of rows are missing in each (18–19 of 42 rows). **May is the problem month.** It has only 42 rows, and 19 have a blank company name. The dataset notes already flag May rows as misaligned or blank, so these look like blank or shifted rows in the source file rather than genuinely unknown values. Excluding May, the remaining missingness is mostly `Stage` (106 of 404 rows, about 26%) and a smaller amount of `Investor` (24 of 404, about 6%).