title: Problem when processing from CSV to CSV with a row count
body: <p>I am trying to process a CSV file into a new CSV file with only columns of interest and remove rows with unfit values of -1. Unfortunately I get unexpected results, as it automatically includes column 0 (old ID) into the new CSV file without explicitly asking the script to do it (as it is not defined in cols = [..]). </p>
  
  <p>How could I change these values for the new row count. That for, when for example we remove row 9 with an id=9, the dataset id goes currently as [..7,8,10...] instead of a new id count as [..7,8,9,10...]. I hope anyone got a solution for it.</p>
  
  <pre><code>import pandas as pd
  
  # take only specific columns from dataset
  cols = [1, 5, 6]
  data = pd.read_csv('data_sample.csv', usecols=cols, header=None) data.columns = ["url", "gender", "age"]
  
  # remove rows from dataset with undefined values of -1
  data = data[data['gender'] != -1]  
  data = data[data['age'] != -1]
  
  """ Additional working solution 
  indexGender = data[data['gender'] == -1].index 
  indexAge = data[data['age'] == -1].index
  
  # Delete the rows indexes from dataFrame 
  data.drop(indexGender,inplace=True) 
  data.drop(indexAge, inplace=True)
  """
  data.to_csv('data_test.csv')
  </code></pre>
  
  <p>Thank you in advance.</p>