title: Search and replace dots and commas in pandas dataframe
body: <p>This is my DataFrame:</p>
  <pre><code>d = {'col1': ['sku 1.1', 'sku 1.2', 'sku 1.3'], 'col2': ['9.876.543,21', 654, '321,01']}
  df = pd.DataFrame(data=d)
  df
  
         col1           col2
  0   sku 1.1   9.876.543,21
  1   sku 1.2            654
  2   sku 1.3         321,01
  </code></pre>
  <p>Data in col2 are numbers in local format, which I would like to convert into:</p>
  <pre><code>      col2
  9876543.21
         654
      321.01
  </code></pre>
  <p>I tried <code>df['col2'] = pd.to_numeric(df['col2'], downcast='float')</code>, which returns a ValueError: : Unable to parse string &quot;9.876.543,21&quot; at position 0.</p>
  <p>I tried also <code>df = df.apply(lambda x: x.str.replace(',', '.'))</code>, which returns ValueError: could not convert string to float: '5.023.654.46'</p>