title: Adding a mode value for nan's using groupBy on another column
body: <p>I have some nan cells in the year column. I thought it'll be better to set the Mode of the year column grouped-By Industry type.</p>
  <pre><code>df
  ID  Name     Industry    Year   Employees Expenses   Profit
  1   E-Zim    Health      2019   320       1,130,700  8553827
  2   Daltfase Software    NaN    78        804,035    13212508
  3   Hotlane  Government  2012   87        1,044,375  8701897
  4   Latho    Health      NaN    103       4,631,808  10727561
  5   Lambam   IT Services 2015   210       4,374,841  4193069
  6   Quozap   Health      2008   21        4,626,275  8179177
  7   Tampware Health      2008   13        2,127,984  3259485
  </code></pre>
  <p>For mode values, i did:</p>
  <pre><code>df_mode_year = df.groupby('Industry')['Year'].apply(lambda x: x.mode().iloc[0])
  df_mode_year
  
  Industry
  Government             2012
  Health                 2008
  IT Services            2015
  Software
  </code></pre>
  <p>And then to modify my df, i tried</p>
  <ol>
  <li>df['Year'].fillna(df_mode_year)</li>
  <li>df['Year'] = df['Year'].fillna(df_mode_year[df['Industry']=='Health'])</li>
  </ol>
  <p>But none of these two are affecting the final df .</p>
  <p>Expected Output:</p>
  <pre><code>df
  ID  Name     Industry    Year   Employees Expenses   Profit
  1   E-Zim    Health      2019   320       1,130,700  8553827
  2   Daltfase Software    NaN    78        804,035    13212508
  3   Hotlane  Government  2012   87        1,044,375  8701897
  4   Latho    Health      2008   103       4,631,808  10727561
  5   Lambam   IT Services 2012   210       4,374,841  4193069
  6   Quozap   Health      2008   21        4,626,275  8179177
  7   Tampware Health      2008   13        2,127,984  3259485
  </code></pre>
  <p>What am i doing wrong?    Thanks a lot.</p>