BUG: Using vanilla NumPy methods on a Modin Dataframe fails

[RehanSD]

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Reproducible Example

# Modin
import modin.pandas as pd
import modin.numpy as np

# Vanilla 
import pandas as vpd
import numpy as vnp

cols = [f"feature_{i}" for i in range(10)]
# This is not enabled in modin.numpy hence using vanilla
npy_array = vnp.random.rand(50, 10)

vdf = vpd.DataFrame(npy_array, columns=cols)
df = pd.DataFrame(vdf)

# Works
tmp = vnp.where(
    df["feature_0"] + df["feature_1"] > df["feature_2"] + df["feature_3"], 1, 0
)

# Doesn't work
tmp = vnp.where(
    df["feature_0"] + df["feature_1"] > df["feature_2"] + df["feature_3"], 1, 0
)
# Doesn't work
tmp = np.where(
    df["feature_0"] + df["feature_1"] > df["feature_2"] + df["feature_3"], 1, 0
)
# Doesn't work
tmp = vnp.where(np.array(df["feature_0"]) + np.array(["feature_1"]) > np.array(df["feature_2"]) + np.array(df["feature_3"]), 1, 0)

Issue Description

We need to fix some of the numpy hooks we provide.

Expected Behavior

This should work - without ExperimentalNumPyAPI on, it should default to pandas, and with it on, it should work distributed.

Error Logs

Replace this line with the error backtrace (if applicable).

Installed Versions

Replace this line with the output of pd.show_versions()