title: Python: clear a specific range of data from a column in a dataframe
body: <p>I have the problem that the dataframe from my import (stock prices from Yahoo) are not correct for a specific time period. I want to clear the data from 2010-01-01 until 2017-10-17 for &quot;VAR1.DE&quot; and replace it empty or with NaN. I have found the panda function &quot;drop&quot; but this will delete the hole column.</p>
  <p>How can I solve the problem?</p>
  <p>Here is my code:</p>
  <pre><code>from pandas_datareader import data as web
  import pandas as pd
  import numpy as np
  from datetime import datetime
  
  assets = ['1211.HK','BABA','BYND','CAP.DE','JKS','PLUG','QCOM','VAR1.DE']
  weights = np.array([0.125,0.125,0.125,0.125,0.125,0.125,0.125,0.125])
  stockStartDate='2010-01-01'
  today = datetime.today().strftime('%Y-%m-%d')
  
  df = pd.DataFrame()
  
  for stock in assets:
   df[stock]=web.DataReader(stock, data_source='yahoo', start=stockStartDate,end=today)['Adj Close']
  </code></pre>