Pandas: ValueError: cannot convert float NaN to integer

For identifying NaN values use boolean indexing:

print(df[df['x'].isnull()])

Then for removing all non-numeric values use to_numeric with parameter errors='coerce' – to replace non-numeric values to NaNs:

df['x'] = pd.to_numeric(df['x'], errors='coerce')

And for remove all rows with NaNs in column x use dropna:

df = df.dropna(subset=['x'])

Last convert values to ints:

df['x'] = df['x'].astype(int)