TL, DR
Sometimes you need to calculate averages, minimums, or other metrics from numeric-only columns in a Pandas DataFrame. Here a few snippets to do it.
Select numeric columns and calculate metrics
You often want to calculate summary statistics like the mean , median , or standard deviation — but you only care about numeric columns.
Trying to apply these functions directly to mixed-type DataFrames can cause issues or return less useful results. Instead, use .select_dtypes() to filter numeric columns before computing:
numeric_mean = df.select_dtypes(include='number').mean()Here’s what’s happening:
select_dtypes(include='number'): selects only numeric columns (int,float, etc.).mean(): calculates the mean across those numeric columns
You can easily swap .mean() with .median(), .std(), or .sum() depending on your needs.
Related links
- Pandas DataFrame.select_dtypes() documentation link
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