title: What is the proper way of combining time series data with metadata in pandas?
body: <p>I have two csv files:</p>
  
  <p><code>customer.csv</code>:</p>
  
  <pre><code>id  name     birthday
  1   Martin   28.04.1990
  2   Twain    30.11.1835
  ....
  </code></pre>
  
  <p>and <code>purchases.csv</code>:</p>
  
  <pre><code>purchase_id    customer_id    item                            price
  1              1              About the ugly German language  3.14
  2              1              Food                            15.92
  3              1              Book                            65.35
  4              2              Stone                           89.79
  </code></pre>
  
  <p>I can load both dataframes as</p>
  
  <pre><code>df_customers = pd.read_csv('customers.csv')
  df_purchases = pd.read_csv('purchases.csv')
  </code></pre>
  
  <p>but how can I combine those two, such that I can easily answer the following questions:</p>
  
  <ul>
  <li>How many items did each customer buy?</li>
  <li>What is the average price of items for each customer?</li>
  </ul>