ENH: Construct pandas dataframe from function

It would be great if we could construct a pd.DataFrame from a function.

Describe the solution you’d like

import pandas as pd
import numpy as np

def my_random():
    return np.random.rand() + 1

df = pd.DataFrame(my_random, index=range(10), columns=range(15))

The output would be equivalent to

col_len = 10
index_len = 15
data = np.array([[my_random() for i in range(col_len)] for j in range(index_len)])
df = pd.DataFrame(data, index=range(index_len), columns=range(columns_len))

Alternatively, we could do the same with something like

df = pd.DataFrame.from_function(my_random, *args, **kwargs)

args and kwargs are passed to the df constructor.

EDIT

I just realized I can easily obtain what I want with

df = pd.DataFrame(index=range(10), columns=range(15)).applymap(
    lambda x: my_random()
)

It’s quite compact and easy to read. It’s slowish but I don’t expect it to be used in high performance tasks.

[MarcoGorelli]

It’s OK 😃 There’s lot’s of other issues open if you want to contribute, see here for how to get started

[jreback]

-1 on this extension, doesn’t provide any new capability and adds to api bloat.