title: why pandas.DataFrame.sum(axis=0) returns sum of values in each column where axis =0 represent rows?
body: <p>In pandas, <strong>axis=0 represent rows</strong> and <strong>axis=1 represent columns</strong>.
  Therefore <strong>to get the sum of values in each row in pandas</strong>, <strong>df.sum(axis=0)</strong> is called.
  <strong>But it returns a sum of values in each columns</strong> and vice-versa. <strong>Why???</strong> </p>
  
  <pre><code>import pandas as pd
  df=pd.DataFrame({"x":[1,2,3,4,5],"y":[2,4,6,8,10]})
  df.sum(axis=0)
  </code></pre>
  
  <p>Dataframe:</p>
  
  <pre><code>   x   y
  0  1   2
  
  1  2   4
  
  2  3   6
  
  3  4   8
  
  4  5  10
  </code></pre>
  
  <p>Output:</p>
  
  <pre><code>x    15
  
  y    30
  </code></pre>
  
  <p>Expected Output:</p>
  
  <pre><code>0     3
  
  1     6
  
  2     9
  
  3    12
  
  4    15
  </code></pre>