title: count specific word in each series of Pandas DataFrame
body: <p>I've been looking for the way to count the occurrence of specific words(dates) in DataFrame. In detail, I'd like to know how many each element in dates_list exists in each columns. Could anyone give me advices ?? Thank you so much.
  I found out the link below but my skill is lack of making use of this.</p>
  <p><a href="https://stackoverflow.com/questions/59475298/counting-specific-keywords-in-a-dataframe">reference</a></p>
  <pre><code>dates_list(No duplicates)
  
  ['2021-06-22', '2021-06-23', '2021-06-24', '2021-06-25', '2021-06-30', '2021-07-01', '2021-07-02', '2021-07-03', '2021-07-04', '2021-07-05', '2021-07-06', '2021-07-07', '2021-07-08', '2021-07-09', '2021-07-10', '2021-07-11', '2021-07-12', '2021-07-13', '2021-07-14', '2021-07-15', '2021-07-16', '2021-07-17', '2021-07-18', '2021-07-19',・・・・・]
  </code></pre>
  <pre><code>push_df
  
  push_a_date,push_b_date,push_c_date,push_d_date
  2021-07-09,2021-07-10,2021-07-14,2021-07-18,
  2021-07-09,2021-07-26,2021-07-30,2021-07-18
  2021-07-22,2021-07-23,2021-07-27,2021-07-31,
  2021-07-23,2021-07-26,2021-07-29,2021-08-02,
  2021-07-24,2021-07-18,2021-07-30,2021-08-03,
  ,,,,,,,,
  </code></pre>
  <pre><code>my ideal output
             push_a_date,push_b_date,push_c_date,push_d_date          
  2021-07-09.   2.            0.         0.         0
  2021-07-18.   0.            1          0.         2
  2021-07-30.   0.            0.         2.         0
  
  </code></pre>