element-wise value comparison noticeably slower for large-scale dataframes
#### Problem Description
element-wise value comparison noticeably slower for large-scale dataframes, compared to corresponding numpy array value comparison (although in older pandas version, the operation speed was acceptable).

```python
import numpy as np
import pandas as pd
x = pd.DataFrame(np.random.rand(3000*4000).reshape((3000,-1)))

# pandas 0.25.1
%timeit x>0.0 
1.72 s ± 3.23 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

# pandas 0.17.1
%timeit x>0.0
115 ms ± 114 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

%timeit x.values>0.0
13.1 ms ± 148 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
```


#### INSTALLED VERSIONS
commit           : None
python           : 3.7.4.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.18.0-80.7.2.el8_0.x86_64
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.1
numpy            : 1.17.2