How can I convert an array of class objects to a dataframe with columns in Pandas?

Question

With the following class:

class Test:
    a : str
    b : str

and the following data frame:

output = pd.DataFrame(columns=['a', 'b']

how can I convert an array, or list, of class Test into a pandas dataframe with matching columns?

Edit:

Let me add a more concrete example:

class Test:
    a: int
    b: int

    def __init__(self, a: int, b: int):
        self.a = a
        self.b = b

l = [Test(10, 20), Test(50, 60)]

output = pd.DataFrame(l,
                  columns=['a', 'b'],
                  index=range(len(l)))

and the error I get is:

ValueError: Shape of passed values is (2, 1), indices imply (2, 2)

Are you having trouble with the typical way to create a DataFrame? For instance, output = pd.DataFrame([test.a, test.b], columns=['a', 'b']), where test = Test() — Stephen B
– Stephen B, Commented Jul 24, 2019 at 22:59
Possible duplicate of Creating a Pandas DataFrame from a Numpy array: How do I specify the index column and column headers? — tim
– tim, Commented Jul 24, 2019 at 23:00
@tim: the questions may be related, but they're not exactly the same since the other question involves part of the list to become the header, which is not the case here — Thomas
– Thomas, Commented Jul 24, 2019 at 23:16
I'm not sure what you intended to do, but Test(10, 20) evaluates to <__main__.Test at 0x1db821405c0> - one element; so pd.DataFrame(l) tells panda to expect one column and two rows, while columns=['a', 'b'] implies two columns. Hence the error. — Jack Fleeting
– Jack Fleeting, Commented Jul 25, 2019 at 0:08

Code Different · Accepted Answer · 2019-07-25 13:43:31Z

3

You can call vars to convert all the attributes of the class into a dict:

class Test:
    def __init__(self, a: int, b: int):
        self.a = a
        self.b = b

tests = [Test(10, 20), Test(50, 60)]
df = pd.DataFrame([vars(t) for t in tests])

edited Jul 25, 2019 at 13:43

answered Jul 25, 2019 at 2:06

Code Different

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4 Comments

Thomas Over a year ago

this is working, thanks! can you explain me the [vars(t)..] section and why it works? kind of new to python, but very new to pandas (like 4 days :))

Thomas Over a year ago

to clarify, I understand vars(t), but I don't understand the vars(t) for ...; I would understand for t in tests: somelist.append(vars(t))

Code Different Over a year ago

It's called list comprehension. Basically a one-liner loop. [vars(t) for t in tests] apply the function vars on every element in tests. Since vars(t) returns a dictionary, [vars(t) for ...] return a list of dictionaries

Thomas Over a year ago

I didn’t know about list comprehension; I’m reading about it now, thanks!

Akaisteph7 · Accepted Answer · 2019-07-25 02:36:07Z

2

Another way to achieve this is to do:

df = pd.DataFrame([test.__dict__ for test in tests])

answered Jul 25, 2019 at 2:36

Akaisteph7

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