fix: access column values instead of DataFrame method

[danielolsen]

Pull Request doc

Purpose

Correct a bug introduced in #507.

What the code is doing

We had meant to access the "diff" column of a DataFrame, but we're instead accessing the .diff() method. This fixes that.

Testing

Tested manually. Before:

>>> from powersimdata import Scenario
>>> from powersimdata.design.investment.investment_costs import (
...     calculate_ac_inv_costs,
...     calculate_gen_inv_costs,
... )
>>> scenario = Scenario(1705)
>>> calculate_ac_inv_costs(scenario)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Users\DanielOlsen\repos\bes\PowerSimData\powersimdata\design\investment\investment_costs.py", line 76, in calculate_ac_inv_costs
    grid_differences.branch = grid_differences.branch.assign(
  File "C:\Python39\lib\site-packages\pandas\core\frame.py", line 3699, in assign
    data[k] = com.apply_if_callable(v, data)
  File "C:\Python39\lib\site-packages\pandas\core\common.py", line 341, in apply_if_callable
    return maybe_callable(obj, **kwargs)
  File "C:\Python39\lib\site-packages\pandas\core\frame.py", line 7260, in diff
    new_data = self._mgr.diff(n=periods, axis=bm_axis)
  File "C:\Python39\lib\site-packages\pandas\core\internals\managers.py", line 567, in diff
    return self.apply("diff", n=n, axis=axis)
  File "C:\Python39\lib\site-packages\pandas\core\internals\managers.py", line 409, in apply
    applied = getattr(b, f)(**kwargs)
  File "C:\Python39\lib\site-packages\pandas\core\internals\blocks.py", line 1272, in diff
    new_values = algos.diff(self.values, n, axis=axis, stacklevel=7)
  File "C:\Python39\lib\site-packages\pandas\core\algorithms.py", line 1918, in diff
    n = int(n)
TypeError: int() argument must be a string, a bytes-like object or a number, not 'DataFrame'
>>> calculate_gen_inv_costs(scenario, 2025, "Moderate")
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Users\DanielOlsen\repos\bes\PowerSimData\powersimdata\design\investment\investment_costs.py", line 393, in calculate_gen_inv_costs
    grid_differences.plant = grid_differences.plant.assign(
  File "C:\Python39\lib\site-packages\pandas\core\frame.py", line 3699, in assign
    data[k] = com.apply_if_callable(v, data)
  File "C:\Python39\lib\site-packages\pandas\core\common.py", line 341, in apply_if_callable
    return maybe_callable(obj, **kwargs)
  File "C:\Python39\lib\site-packages\pandas\core\frame.py", line 7260, in diff
    new_data = self._mgr.diff(n=periods, axis=bm_axis)
  File "C:\Python39\lib\site-packages\pandas\core\internals\managers.py", line 567, in diff
    return self.apply("diff", n=n, axis=axis)
  File "C:\Python39\lib\site-packages\pandas\core\internals\managers.py", line 409, in apply
    applied = getattr(b, f)(**kwargs)
  File "C:\Python39\lib\site-packages\pandas\core\internals\blocks.py", line 1272, in diff
    new_values = algos.diff(self.values, n, axis=axis, stacklevel=7)
  File "C:\Python39\lib\site-packages\pandas\core\algorithms.py", line 1918, in diff
    n = int(n)
TypeError: int() argument must be a string, a bytes-like object or a number, not 'DataFrame'

After:

>>> from powersimdata import Scenario
>>> from powersimdata.design.investment.investment_costs import (
...     calculate_ac_inv_costs,
...     calculate_gen_inv_costs,
... )
>>> scenario = Scenario(1705)
>>> calculate_ac_inv_costs(scenario)
{'line_cost': 292542221726.4701, 'transformer_cost': 7594541147.697944}
>>> calculate_gen_inv_costs(scenario, 2025, "Moderate")
Technology
coal          2.750677e+10
geothermal    7.362562e+08
hydro         1.492064e+10
ng            5.826340e+10
nuclear       1.592516e+10
solar         5.741915e+11
wind          7.455055e+11
Name: cost, dtype: float64

Time estimate

2 minutes.

[rouille]

I always do df["A"] to access column instead of df.A for the reason you just brought