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29. Python in Excel

29.4 Python Object or Excel Value: Choosing the Output Type

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Example first. Zoya runs df[["Qty", "Amount", "Mins"]].describe() and the cell shows just the word DataFrame with a small card icon. Her manager wants the numbers on the sheet. She presses Ctrl+Alt+Shift+M and the same result spills into 9 rows and 4 columns of normal Excel values that she can format, chart and reference. Same code, two output types. Choosing the right one is the skill.

Python output types — in 30 seconds

What: A Python cell can return its result as a Python object (the cell shows a card icon and a type name such as DataFrame) or as Excel values (the result spills into the grid like a dynamic array).

Why: Python objects are best for results you will reuse in more Python cells; Excel values are needed for charts, formulas and conditional formatting. Large spills can also hit #SPILL! if cells are not empty.

Tiny example: df[["Qty", "Amount", "Mins"]].describe() as an object shows DataFrame; as Excel values it spills 9 rows × 4 columns, for example mean Amount 287 and max 1299.

First look at the data (before → after):

Python output types: before and after tables, fictional Blinkit Maharashtra data

Expected result — Output: Excel values (spilled, rounded here)

— Qty Amount Mins
count 10 10 10
mean 2.4 287 12.8
min 1 64 8
max 5 1299 18
Before table and formula as text

Before — Output: Python object

Cell Shows
A15 [card] DataFrame

Formula / click path

Python output menu in the formula bar › Excel Value
or Ctrl+Alt+Shift+M
or right-click › Python Output

Do it step by step:

  1. In A15 write the describe code from the box below and commit with Ctrl+Enter. The cell shows a card icon and DataFrame.
  2. Select the card icon (or press Ctrl+Shift+F5) to preview the table without changing the output.
  3. Make sure the 9 × 4 area from A15 down and right is empty, so the spill has room.
  4. Press Ctrl+Alt+Shift+M, or open the Python output menu in the formula bar and choose Excel Value.
  5. The numbers spill into A15:D23. Format them with 2 decimals and refer to them with normal formulas, for example =C17 for the mean Amount.
  6. Press Ctrl+Alt+Shift+M again to switch back to a Python object.

The describe() result in full

df[["Qty", "Amount", "Mins"]].describe()
Qty Amount Mins
count 10 10 10
mean 2.4 287 12.8
std 1.35 362.29 3.43
min 1 64 8
25% 1.25 120 10.25
50% 2 207.5 12.5
75% 3 238 15.5
max 5 1299 18

Expected output computed by running this exact code locally with pandas on the same fictional data (Python in Excel runs it in the Microsoft Cloud; numbers are the same, the look of the card may differ). Values are rounded to 2 decimals here; Excel shows more digits until you format them. std is the sample standard deviation (the same as Excel's STDEV.S), and 25%/50%/75% are quartiles calculated the same way as Excel's QUARTILE.INC.

Why does the first column show count, mean, std…? Microsoft explains that when a DataFrame is returned as Excel values, the index column is included only if its values are not numbers (like the result of describe() or a groupby) or if the index has a name. For a plain df.head(3) the 0, 1, 2 index is left out.

Which output when?

Situation Choose Reason
The result feeds another Python cell (a cleaned df, a model) Python object Keeps the full object; Microsoft recommends objects for reuse
You want an Excel chart, conditional formatting or a formula on it Excel value Excel tools need values in cells
A single number such as a total Either A number always shows as a number
A chart (Matplotlib or seaborn) Object, then Display Plot over Cells, or Excel Value for an in-cell picture Lesson 29.6
A very large DataFrame Python object A huge spill slows the workbook and blocks cells

#SPILL! with Python. When the output is Excel values and any cell in the spill area already has something in it, the Python cell returns #SPILL! instead of the result, exactly like a FILTER formula would. Clear the cells or move the Python cell.

Check the spilled numbers with Excel

Spilled value Excel check Result
mean Amount =AVERAGE(tblOrders[Amount]) 287
std Amount =STDEV.S(tblOrders[Amount]) 362.29
50% Mins (median) =MEDIAN(tblOrders[Mins]) 12.5
75% Mins =QUARTILE.INC(tblOrders[Mins],3) 15.5

Microsoft sources (checked 7 October 2026): Get started with Python in Excel; Python in Excel DataFrames; Python in Excel keyboard shortcuts.

Practice task (try it before you open the answer):

  1. Return df["Amount"].describe() (one column) as Excel values.
  2. Which value is the median and what is it?
  3. Write the Excel formula that checks the 25% value.
Answer
  1. It spills 8 rows (count, mean, std, min, 25%, 50%, 75%, max) with the labels in the first column.
  2. The 50% row is the median: 207.5.
  3. =QUARTILE.INC(tblOrders[Amount],1) returns 120.

Ravindra Bagale's Tip

Keep working results as Python objects and turn only the final table into Excel values. Your sheet stays light and the numbers your manager sees are real cells.