Pandas: How to drop multiple columns with nan as col name?

Question

As per the title here's a reproducible example:

raw_data = {'x': ['this', 'that', 'this', 'that', 'this'], 
            np.nan: [np.nan, np.nan, np.nan, np.nan, np.nan], 
            'y': [np.nan, np.nan, np.nan, np.nan, np.nan],
            np.nan: [np.nan, np.nan, np.nan, np.nan, np.nan]}

df = pd.DataFrame(raw_data, columns = ['x', np.nan, 'y', np.nan])
df

   x     NaN  y    NaN
0  this  NaN  NaN  NaN
1  that  NaN  NaN  NaN
2  this  NaN  NaN  NaN
3  that  NaN  NaN  NaN
4  this  NaN  NaN  NaN

Aim is to drop only the columns with nan as the col name (so keep column y). dropna() doesn't work as it conditions on the nan values in the column, not nan as the col name.

df.drop(np.nan, axis=1, inplace=True) works if there's a single column in the data with nan as the col name, but not with multiple columns with nan as the col name, as in my data.

So how to drop multiple columns where the col name is nan?

Answer 1

In [218]: df = df.loc[:, df.columns.notna()]

In [219]: df
Out[219]:
      x   y
0  this NaN
1  that NaN
2  this NaN
3  that NaN
4  this NaN