title: Pandas: how to change all the values of a column?
body: <p>I have a data frame with a column called <code>"Date"</code> and want all the values from this column to have the same value (the year only). Example:</p>
  
  <pre><code>City     Date
  Paris    01/04/2004
  Lisbon   01/09/2004
  Madrid   2004
  Pekin    31/2004
  </code></pre>
  
  <p>What I want is:</p>
  
  <pre><code>City     Date
  Paris    2004
  Lisbon   2004
  Madrid   2004
  Pekin    2004
  </code></pre>
  
  <p>Here is my code:</p>
  
  <pre><code>fr61_70xls = pd.ExcelFile('AMADEUS FRANCE 1961-1970.xlsx')
  
  #Here we import the individual sheets and clean the sheets    
  years=(['1961','1962','1963','1964','1965','1966','1967','1968','1969','1970'])
  
  fr={}
  
  header=(['City','Country','NACE','Cons','Last_year','Op_Rev_EUR_Last_avail_yr','BvD_Indep_Indic','GUO_Name','Legal_status','Date_of_incorporation','Legal_status_date'])
  
  for year in years:
      # save every sheet in variable fr['1961'], fr['1962'] and so on
      fr[year]=fr61_70xls.parse(year,header=0,parse_cols=10)
      fr[year].columns=header
      # drop the entire Legal status date column
      fr[year]=fr[year].drop(['Legal_status_date','Date_of_incorporation'],axis=1)
      # drop every row where GUO Name is empty
      fr[year]=fr[year].dropna(axis=0,how='all',subset=[['GUO_Name']])
      fr[year]=fr[year].set_index(['GUO_Name','Date_of_incorporation'])
  </code></pre>
  
  <p><em>It happens that in my DataFrames, called for example <code>fr['1961']</code> the values of <code>Date_of_incorporation</code> can be anything (strings, integer, and so on), so maybe it would be best to completely erase this column and then attach another column with only the year to the DataFrames?</em></p>