Forecast Q4 revenue by product
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POST /v1/cells
curl https://api.quadratichq.com/v1/cells \n -H "Authorization: Bearer ..." \n -d '{\n "file": "q3-forecast",\n "range": "A1:B2",\n "values": [["Revenue","MRR"],[1200,980]]\n }'
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A
B
C
D
E
1
Product
Revenue
Growth
Forecast
Notes
2
Widget
$1.2M
+18%
$1.4M
Strong
3
Gadget
890000
+12%
$997K
Steady
4
Gizmo
540000
-3%
$524K
Flat
5
Rocket
2100000
$2.6M
Top line
6
Anvil
330000
$356K
Stable
7
Dynamite
180000
#REF!
Fast grow
8
TOTAL
5240000
#REF!
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B2 · Python
Thinking…
df = q.cells("A1:E500", first_row_header=True)
result = (
df[df["churned"] == False]
.groupby(["segment", "region"])
.agg(revenue=(("arr", "sum")))
.nlargest(5, "revenue")
)
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