How to get the mean and median of derived value

Question

I have a DataFrame of houses in different towns:

data = [
  ['Oxford', 2016, True],
  ['Oxford', 2016, True],
  ['Oxford', 2018, False],
  ['Cambridge', 2016, False],
  ['Cambridge', 2016, True],
  ['Brighton', 2019, True],
]
df = pd.DataFrame(data, columns=['town', 'year_built', 'is_detached'])

I want to get the mean and median number of houses per town.

How can I do this?

I know how to get the mean (hackily):

len(df) / len(df.town.value_counts())

But I don't know how to get the median.

[Duplicate Question](https://stackoverflow.com/questions/24101524/finding-median-of-list-in-python) — mccurcio, Nov 19 '22 at 02:29

score 2 · Accepted Answer · edited Nov 19 '22 at 02:25

2

Use value_counts to get the number of houses per town, and then agg with 'mean' and 'median':

df['town'].value_counts().agg(['mean', 'median'])

Output:

mean      2.0
median    2.0
Name: town, dtype: float64

edited Nov 19 '22 at 02:25

Peter Mortensen

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answered Oct 20 '22 at 07:43

mozway

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How to get the mean and median of derived value

1 Answers1