title: How to create pandas.date_range() for each row from column "start_date" and column "end_date"?
body: <p>I have a df like:</p>
  <pre><code>id | start_date | end_date  | price
  1  | 2020-10-01 | 2020-10-3 | 1
  1  | 2020-10-03 | 2020-10-4 | 1
  2  | 2020-10-04 | 2020-10-6 | 2
  3  | 2020-10-05 | 2020-10-5 | 3
  </code></pre>
  <p>Columns &quot;start_date&quot; and &quot;end_date&quot; are datetime64[ns].</p>
  <p>I want to create a &quot;date&quot; column from the date range.</p>
  <p>Easiest way is creating a pandas.date_range(start_date, end_date, freq=&quot;D&quot;), then using .explode().</p>
  <p>End result should look like:</p>
  <pre><code>id | start_date | end_date  | price | date
  1  | 2020-10-01 | 2020-10-3 | 1     | 2020-10-01
  1  | 2020-10-01 | 2020-10-3 | 1     | 2020-10-02
  1  | 2020-10-01 | 2020-10-3 | 1     | 2020-10-03
  1  | 2020-10-03 | 2020-10-4 | 1     | 2020-10-03
  1  | 2020-10-03 | 2020-10-4 | 1     | 2020-10-04
  2  | 2020-10-04 | 2020-10-6 | 2     | 2020-10-04
  2  | 2020-10-04 | 2020-10-6 | 2     | 2020-10-05
  2  | 2020-10-04 | 2020-10-6 | 2     | 2020-10-06
  3  | 2020-10-05 | 2020-10-5 | 3     | 2020-10-05
  </code></pre>
  <p>Tried so far:</p>
  <pre><code>df[&quot;daterange&quot;] = pd.date_range(df[&quot;start_date&quot;], df[&quot;end_date&quot;])
  </code></pre>
  <blockquote>
  <p>TypeError: Cannot convert input [0 2020-10-01
  1 2020-10-01</p>
  </blockquote>
  <pre><code>for row in df.itertuples():
      df[&quot;daterange&quot;] = pd.date_range(start=row.start_date, end=row.end_date)
  </code></pre>
  <blockquote>
  <p>ValueError: Length of values (3) does not match length of index (9)</p>
  </blockquote>
  <p><strong>Lambdas, apply, melt, etc. is way too slow for my dataframe size and is not useable!</strong></p>
  <p>/edit</p>
  <p>Fastet method I found so far:</p>
  <pre><code>https://github.com/Garve/scikit-bonus
  skbonus.pandas.preprocessing.DateTimeExploder(
          &quot;date&quot;,
          start_column=&quot;start_date&quot;,
          end_column=&quot;end_date&quot;,
          frequency=&quot;d&quot;,
          drop=False,
      )
  </code></pre>