title: Pandas - Add many new columns based on many aggregate functions
body: <p>Pandas 1.0.5</p>
  <pre><code>import pandas as pd
  d = pd.DataFrame({
      &quot;card_id&quot;: [1, 1, 2, 2, 1, 1, 2, 2],
      &quot;day&quot;: [1, 1, 1, 1, 2, 2, 2, 2],
      &quot;amount&quot;: [1, 2, 10, 20, 3, 4, 30, 40]
    })
  
  #add columns
  d['count'] = d.groupby(['card_id', 'day'])[&quot;amount&quot;].transform('count')
  d['min'] = d.groupby(['card_id', 'day'])[&quot;amount&quot;].transform('min')
  d['max'] = d.groupby(['card_id', 'day'])[&quot;amount&quot;].transform('max')
  </code></pre>
  <p>I would like to change the three transform lines to one line.  I tried this:</p>
  <pre><code>d['count', 'min', 'max'] = d.groupby(['card_id', 'day'])[&quot;amount&quot;].transform('count', 'min', 'max')
  </code></pre>
  <p>Error: &quot;TypeError: count() takes 1 positional argument but 3 were given&quot;</p>
  <p>I also tried this:</p>
  <pre><code>d[('count', 'min', 'max')] = d.groupby(['card_id', 'day']).agg(
      count = pd.NamedAgg('amount', 'count')
      ,min = pd.NamedAgg('amount', 'min')
      ,max = pd.NamedAgg('amount', 'max')
  )
  </code></pre>
  <p>Error: &quot;TypeError: incompatible index of inserted column with frame index&quot;</p>