Converting a pint.Quantity to PintArray when adding to a pd.DataFrame

[Musaefendic]

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?

[andrewgsavage]

An ExtensionArray must have a defined length, making your suggestion not possible.

Yes, it would be very nice to have. To get this work, pandas needs to identify the quantity as a scalar of PintType, then try to construct a PintArray.
pandas-dev/pandas#27995