Is there an easy way to construct a pandas DataFrame from an Iterable of attrs objects?-CodePudding

One can do that with dataclasses like so:

from dataclasses import dataclass
import pandas as pd

@dataclass
class MyDataClass:
    i: int
    s: str


df = pd.DataFrame([MyDataClass("a", 1), MyDataClass("b", 2)])

that makes the DataFrame df with columns i and s as one would expect.

Is there an easy way to do that with an attrs class?

I can do it by iterating over the the object's properties and constructing an object of a type like dict[str, list] ({"i": [1, 2], "s": ["a", "b"]} in this case) and constructing the DataFrame from that but it would be nice to have support for attrs objects directly.

CodePudding user response：

You can access the dictionary at the heart of a dataclass like so

a = MyDataClass("a", 1)
a.__dict__

this outputs:

{'i': 'a', 's': 1}

Knowing this, if you have an iterable arr of type MyDataClass, you can access the __dict__ attribute and construct a dataframe

arr = [MyDataClass("a", 1), MyDataClass("b", 2)]
df = pd.DataFrame([x.__dict__ for x in arr])

df outputs:

   i  s
0  a  1
1  b  2

The limitation with this approach that if the slots option is used, then this will not work.

Alternatively, it is possible to convert the data from a dataclass to a tuple or dictionary using dataclasses.astuple and dataclasses.asdict respectively.

The data frame can be also constructed using either of the following:

# using astuple
df = pd.DataFrame(
  [dataclasses.astuple(x) for x in arr], 
  columns=[f.name for f in dataclasses.fields(MyDataClass)]
)

# using asdict
df = pd.DataFrame([dataclasses.asdict(x) for x in arr])