Pandas how to change all the values of a column

Question

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

User · Answer

You can do a column transformation by using apply

Define a clean function to remove the dollar and commas and convert your data to float.

def clean(x):
    x = x.replace("$", "").replace(",", "").replace(" ", "")
    return float(x)

Next, call it on your column like this.

data['Revenue'] = data['Revenue'].apply(clean)

User · Answer

As  DSM points out  you can do this more directly using the vectorised string methods  df  Date   str -4   astype int   Or using extract  assuming there is only one set of digits of length 4 somewhere in each string   df  Date   str extract    P lt year gt  d 4     astype int   An alternative slightly more flexible way  might be to use apply  or equivalently map  to do this  df  Date     df  Date   apply lambda x  int str x  -4                     converts the last 4 characters of the string to an integer  The lambda function  is taking the input from the Date and converting it to a year  You could  and perhaps should  write this more verbosely as  def convert to year date in some format       date as string   str date in some format     cast to string     year as string   date in some format -4     last four characters     return int year as string   df  Date     df  Date   apply convert to year   Perhaps  Year  is a better name for this column

User · Answer

Or if one want to use lambda function in the apply function   data  Revenue   data  Revenue   apply lambda x float x replace         replace          replace

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

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