[Python] Pandas FutureWarning about concatenating DFs with NAs seems biased

I am getting Future Warning with Pandas 2.2.2 when I try to concatenate DFs with Floating Values and Nones.

But the same won't happen if I use INT instead of FLOAT

import pandas as pd

# Block with INT
df1 = pd.DataFrame({'A': [1], 'B': [4]})
df2 = pd.DataFrame({'A': [2], 'B': [None]})
print(len(pd.concat([df1, df2])))

# Block with FLOAT
df1 = pd.DataFrame({'A': [1], 'B': [4.0]})
df2 = pd.DataFrame({'A': [2], 'B': [None]})
print(len(pd.concat([df1, df2])))


Block with INT runs fine, while Block with FLOAT gives warning

Sample output

2
./test.py:18: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
print(len(pd.concat([df1, df2])))
2


Is it expected?

It doesn't feel like what the warning is trying to convey.

Also, I have valid content in other columns, why should this create noise.

I don't think this is duplicate of this: Alternative to .concat() of empty dataframe, now that it is being deprecated?

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