title: Cross Tabulation for categorical values in Pandas
body: <p>In below example, frequency of two categorical values are taken together i.e.'default' and 'housing'-</p>
  
  <pre><code>pd.crosstab(bd['default'],bd['housing'])
  
  </code></pre>
  
  <p><strong>housing</strong>        <strong>no</strong>   <strong>yes</strong></p>
  
  <p><strong>default</strong></p>
  
  <p><strong>no</strong>            19701   24695 </p>
  
  <p><strong>yes</strong>          380     435</p>
  
  <p>In the above frequency table, we observe that there are 24695 observations where the value for 'housing' is 'yes' and 'default' is 'no'.This is a huge chunk of the population. There is a smaller chunk of about 435 observations where housing is 'yes' and default is 'yes'as well. Within the observations where default is 'yes', 'housing' is 'yes' for a higher number of observations i.e. 435 as compared to where housing is 'no' i.e. 380.</p>
  
  <p>so i found above explanation in one example but i could not understand the table properly .are they also saying that there are 19701 observation for housing where value is 'no'</p>
  
  <p>Can someone please brief me in simple words or other interpretations what are the observation above?</p>