Pandas: how to change all the values of a column?

I have a data frame with a column called `"Date"` and want all the values from this column to have the same value (the year only). Example:

City Date
Paris 01/04/2004
Lisbon 01/09/2004
Madrid 2004
Pekin 31/2004

What I want is:

City Date
Paris 2004
Lisbon 2004
Madrid 2004
Pekin 2004

Here is my 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'])

*It happens that in my DataFrames, called for example `fr['1961']` the values of `Date_of_incorporation` 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?*