table from wikipedia

[snippsat]

If look at Rank column df2['Rank'],see that not all countries get a Rank number but -.
This is correct as you see the same on website.
Change line 10 to this:

df0 = pd.read_html(str(sov_tables), na_values='–')

Do df2.dtypes

Output:
Rank                     float64
Country name              object
Population                 int64
Date                      object
% of world population     object
dtype: object

No int because of NaN values.
If need int most drop NaN with dropna().

df2['Rank'] = df2['Rank'].astype('int')

For Date do this.

df2['Date'] = pd.to_datetime(df2['Date'])

Output:
Rank                              int32
Country name                     object
Population                        int64
Date                     datetime64[ns]
% of world population            object

One to go.