- Applying `pd.to_datetime()` to a column using `mutate` seems to fail

siuba-datetime-example.py

import pandas as pd
from siuba import *

my_data = {
    'name': ["Abigail Adams"],
    'birth': ["1744-11-22"],
    'death': ["1818-10-28"]
}

df = pd.DataFrame(my_data)

# This pipeline will raise an error:
#   TypeError: Symbolic objects can not be converted to True/False, or used with these keywords: not, and, or.
(
    df
    >> mutate(birth_dt = pd.to_datetime(_.birth))
)

siuba-filter-example.py

import pandas as pd
from siuba import filter
from siuba import _

my_data = pd.DataFrame({
    'dates': ["1776-07-04", pd.NA]
})

# The pipeline below gives "TypeError: Cannot perform 'rand_' with a dtyped [object] array and scalar of type [bool]"
(
    my_data
    >> filter(_.dates)
)

siuba-mpg-class-bug.py

from plotnine.data import mpg
from siuba import rename

# This fails with an "invalid syntax" error
model = (
    mpg
    >> rename(car_class = _.class)
)

siuba_pop_example.py

import pandas as pd
from siuba import *

my_data = pd.DataFrame({
    "pop": [1, 2, 3]
})

(
    my_data
    >> mutate(pop_doubled = _.pop * 2)
) # TypeError: unsupported operand type(s) for *: 'method' and 'int'

statsmodels-class-bug.py

import statsmodels.formula.api as smf

from plotnine.data import mpg

# You'll get a syntax error, and I think it's because `class`
#   is a reserved keyword in Python, even though it's also
#   the name of a variable in the dataset.
model = smf.ols("cty ~ hwy + class", data=mpg)