title: python dataframe, groupby based on one column and fill null values from another column using last non-null value
body: <p>I have a dataframe that has values for names based on multiple dates. I have created a series of null values for each name on a new date, and want to fill null values of one column based on the last non-null value for that name.</p>
  <pre><code>data = {'name':  ['Alex', 'Ben', 'Marry','Alex', 'Ben', 'Marry'],
          'job': ['teacher', 'doctor', 'engineer','teacher', 'doctor', 'engineer'],
          'age': ['27', '32', '78','27', '32', '78'],
          'weight': ['160', '209', '130','164', '206', '132'],
          'date': ['6-12-2022', '6-12-2022', '6-12-2022','6-13-2022', '6-13-2022', '6-13-2022']
          }
  
  df = pd.DataFrame(data)
  df
  </code></pre>
  <p>After adding null values:</p>
  <pre><code>    |name   |job        |age|weight |date
  |---|-------|-----------|---|-------|--------
  |0  |Alex   |teacher    |27 |160    |6-12-2022
  |1  |Ben    |doctor     |32 |209    |6-12-2022
  |2  |Marry  |engineer   |78 |130    |6-12-2022
  |3  |Alex   |teacher    |27 |164    |6-13-2022
  |4  |Ben    |doctor     |32 |206    |6-13-2022
  |5  |Marry  |engineer   |78 |132    |6-13-2022
  |6  |Alex   |NaN        |NaN|NaN    |6-14-2022
  |7  |Ben    |NaN        |NaN|NaN    |6-14-2022
  |8  |Marry  |NaN        |NaN|NaN    |6-14-2022
  </code></pre>
  <p>Now I need to fill null values for job, and age based on last entered value for that name.</p>
  <p>Appreciate your help</p>
  <p>Thanks</p>