title: Google BigQuery Schema conflict (pyarrow error) with Numeric data type using load_table_from_dataframe
body: <p>I got the following error when I upload numeric data (int64 or float64) from a Pandas dataframe to a <em>&quot;Numeric&quot;</em> Google BigQuery Data Type:</p>
  <blockquote>
  <p>pyarrow.lib.ArrowInvalid: Got bytestring of length 8 (expected 16)</p>
  </blockquote>
  <p>I tried to change the datatype of 'tt' field from Pandas dataframe without results:</p>
  <pre><code>df_data_f['tt'] = df_data_f['tt'].astype('float64')
  </code></pre>
  <p>and</p>
  <pre><code>df_data_f['tt'] = df_data_f['tt'].astype('int64')
  </code></pre>
  <p>Using the schema:</p>
  <pre><code> job_config.schema = [
                      ...             
                      bigquery.SchemaField('tt', 'NUMERIC')
                      ...]
  </code></pre>
  <hr />
  <p>Reading this <a href="https://github.com/googleapis/google-cloud-python/issues/7370" rel="nofollow noreferrer">google-cloud-python issues report</a> I got:</p>
  <blockquote>
  <p>NUMERIC   = pyarrow.decimal128(38, 9)</p>
  </blockquote>
  <p>Therefore the <em>&quot;Numeric&quot;</em> Google BigQuery Data Type uses more bytes than &quot;float64&quot; or &quot;int64&quot;, and that is why pyarrow can't match the datatypes.</p>
  <hr />
  <p>I have:</p>
  <blockquote>
  <p>Python 3.6.4</p>
  <p>pandas                    1.0.3</p>
  <p>pyarrow                   0.17.0</p>
  <p>google-cloud-bigquery     1.24.0</p>
  </blockquote>