title: How to remove Empty Cell from data frame row wise
body: <p>I have csv data in the following format</p>
  
  <pre><code>ab   aback  abandon  abate  Class
  ab   NaN    abandon  NaN    A
  NaN  aback  NaN      NaN    A
  NaN  aback  abandon  NaN    B
  ab   NaN    NaN      abate  C
  NaN  NaN    abandon  abate  C
  </code></pre>
  
  <p>I want to remove the NaN cell and re-arrange the data as </p>
  
  <pre><code>ab  abandon A
  aback   A   
  aback   abandon B
  ab  abate   C
  abandon abate   C
  </code></pre>
  
  <p>The headers are not required in the processed form. I tried a number of threads such as <a href="https://stackoverflow.com/questions/20235401/remove-nan-from-pandas-series">Remove NaN from pandas series</a>, <a href="https://chrisalbon.com/python/pandas_missing_data.html%7Dhttps://chrisalbon.com/python/pandas_missing_data.htm" rel="nofollow noreferrer">Missing Data In Pandas Dataframes</a>, <a href="https://stackoverflow.com/questions/21011777/how-can-i-remove-nan-from-list-python-numpy">How can I remove Nan from list Python/NumPy</a> etc. but they are all providing column wise solution. </p>
  
  <p><a href="https://drive.google.com/file/d/0B7PsfqmAuYkwcy1HRENrQjRDdlU/view?usp=sharing" rel="nofollow noreferrer">here is the sample file</a>.
  It has empty cells and when I display it using dataframe, all the empty cells are shown as NaN
  Here is the code</p>
  
  <pre><code>import pandas as pd
  
  df = pd.read_csv('C:/Users/ABRAR/Google Drive/Tourism Project/Small_sample.csv', low_memory=False)
  print(df) 
  </code></pre>