Why is first argument sometimes rows and sometimes columns?

[Mark17]

I can do this:

# creating a value with all null values in new data frame 
new["Null Column"]= None

In this example, the first argument in brackets calls for a column.

I can also do this:

>>>df = pd.DataFrame([[1, 2], [4, 5], [7, 8]],
...  index=['cobra', 'viper', 'sidewinder'],
...  columns=['max_speed', 'shield'])

>>>df.loc['viper']
max_speed    4
shield       5
Name: viper, dtype: int64

In this example, the first argument in brackets references a row.

Is it accurate to say in more general terms that .loc and .iloc methods (and maybe others?) call for (row, column) whereas subsetting/slicing methods/syntax call for (column, row)?

If so, then is there a reason why it's not more consistent?