BUG: Weird behavior for comparison operations `eq` and `ne`
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
import pandas as pd
import numpy as np
random_state = np.random.RandomState(seed=42)
ncols = 64
nrows = 156
test_data = {
    "col{}".format(int(i)): random_state.randint(
        0, 100, size=(nrows)
    )
    for i in range(ncols)
}
df = pd.DataFrame(test_data)
df.eq("a") # it works good
nrows = 157 # change row count
test_data = {
    "col{}".format(int(i)): random_state.randint(
        0, 100, size=(nrows)
    )
    for i in range(ncols)
}
df = pd.DataFrame(test_data)
df.eq("a") # it doesn't work
# ValueError: unknown type str32
nrows = 156 # return row count to valid value
ncols = 65 # change col count
test_data = {
    "col{}".format(int(i)): random_state.randint(
        0, 100, size=(nrows)
    )
    for i in range(ncols)
}
df = pd.DataFrame(test_data)
df.eq("a") # it doesn't work as well
# ValueError: unknown type str32
```

#### Problem description

Looks like the problem is related to size of operands for comparison operations. Could anyone explain please? Is it normal behavior?

#### Output of ``pd.show_versions()``

<details>

pandas : 1.1.2
numpy : 1.18.4
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 41.2.0
Cython : None
pytest : 5.4.2
hypothesis : None
sphinx : None
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.5.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.14.0
pandas_datareader: None
bs4 : 4.9.1
bottleneck : None
fsspec : 0.7.3
fastparquet : None
gcsfs : None
matplotlib : 3.2.1
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : 0.16.0
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.4.1
sqlalchemy : 1.3.17
tables : 3.6.1
tabulate : None
xarray : 0.15.1
xlrd : 1.2.0
xlwt : None
numba : None

</details>
