title: How to combine two dataframes vertically with only some columns in common using Pandas?
body: <p>Let's say I have two data frame and I want to combine them (more like concatenating than merging since I am not joining on any columns). Here is a made-up example:</p>
  
  <p>Here is table 1:</p>
  
  <pre><code>player_name   points  rebounds  assists
  player1       27.0    9.0       9.0
  player2       31.0    4.0       5.0
  player3       15.0    10.0      1.0
  </code></pre>
  
  <p>Here is table 2:</p>
  
  <pre><code>player_name   points  height  weight
  player4       17.0    6'0"    200
  player5       21.0    6'2"    230
  player6       26.0    6'5"    270
  </code></pre>
  
  <p>Here is the resulting table:</p>
  
  <pre><code>player_name   points  rebounds  assists  height  weight  
  player1       27.0    9.0       9.0      Null    Null
  player2       31.0    4.0       5.0      Null    Null
  player3       15.0    10.0      1.0      Null    Null
  player4       17.0    Null      Null     6'0"    200
  player5       21.0    Null      Null     6'2"    230
  player6       26.0    Null      Null     6'5"    270
  </code></pre>
  
  <p>Basically, both tables do not have the same columns, and that is okay. I want to retain all the columns from each of the tables (combining the ones in common, such as points in this case), and fill in Null values for the ones not in common. How can I do this simply in Python/Pandas? This is slightly different than a simple df join or concatenate, from my understanding. </p>