Converting a pint.Quantity to PintArray when adding to a pd.DataFrame #248
Description
Description
I tried adding a pint.Quantity to an existing pd.DataFrame, thinking that pint-pandas might transform the Quantity into a PintArray that:
- matches the number of rows
- preserves the unit.
Reproducible Example
import pandas as pd
from pint_pandas import PintArray, Quantity
# Existing pd.DataFrame
data = {"bar": [0.07, 0.30, 0.85, 1.00]}
df = pd.DataFrame(data)
# Trying to add a `pint.Quantity`
df['content'] = Quantity(42.0, units='percent')
df.dtypes
# Output:
# bar float64
# content object # <---- Expected: pint[percent]output:
| bar | content | |
|---|---|---|
| 0 | 0.07 | 42.0 percent |
| 1 | 0.30 | 42.0 percent |
| 2 | 0.85 | 42.0 percent |
| 3 | 1.00 | 42.0 percent |
Question
The documentation indeed suggests using a pd.Series or a PintArray to achieve this, but this approach feels a bit verbose. I’d like to add a new column directly with just Quantity to mimic the pandas API when creating a new column from a float to an existing pd.DataFrame.
Would it make sense to convert a pint.Quantity into a PintArray when adding it to a pd.DataFrame?