Replacing column values in a pandas DataFrame

Question

I m trying to replace the values in one column of a dataframe  The column   female   only contains the values  female  and  male     I have tried the following   w  female    female    1  w  female    male    0     But receive the exact same copy of the previous results   I would ideally like to get some output which resembles the following loop element-wise   if w  female      female       w  female      1   else      w  female      0     I ve looked through the gotchas documentation  http   pandas pydata org pandas-docs stable gotchas html  but cannot figure out why nothing happens   Any help will be appreciated

User · Answer

This is very compact   w  female   w  female       female   1 w  female   w  female       male   0   Another good one   w  female     w  female   replace regex  female   value 1  w  female     w  female   replace regex  male   value 0

User · Answer

w replace   female    female  1   male  0    inplace   True   The above code will replace  female  with 1 and  male  with 0  only in the column  female

User · Answer

w female replace to replace dict female 1  male 0   inplace True    See pandas DataFrame replace   docs

User · Answer

Slight variation   w female replace   male    female     1  0   inplace True

User · Answer

If I understand right  you want something like this   w  female     w  female   map   female   1   male   0      Here I convert the values to numbers instead of strings containing numbers   You can convert them to  1  and  0   if you really want  but I m not sure why you d want that    The reason your code doesn t work is because using   female   on a column  the second  female  in your w  female    female    doesn t mean  select rows where the value is  female     It means to select rows where the index is  female   of which there may not be any in your DataFrame

User · Answer

I think that in answer should be pointed which type of object do you get in all methods suggested above  is it Series or DataFrame   When you get column by w female  or w  2    where  suppose  2 is number of your column  you ll get back DataFrame  So in this case you can use DataFrame methods like  replace   When you use  loc or iloc you get back Series  and Series don t have  replace method  so you should use methods like apply  map and so on

User · Answer

There is also a function in pandas called factorize which you can use to automatically do this type of work  It converts labels to numbers    male    female    male   - gt   0  1  0   See this answer for more information

User · Answer

This should also work   w female w female     female     1  w female w female     male       0

User · Answer

You can also use apply with  get i e   w  female     w  female   apply   male  0   female  1  get    w   pd DataFrame   female    female   male   female     print w    Dataframe w      female 0  female 1    male 2  female   Using apply to replace values from the dictionary   w  female     w  female   apply   male  0   female  1  get  print w    Result      female 0       1 1       0 2       1    Note  apply with dictionary should be used if all the possible values of the columns in the dataframe are defined in the dictionary else  it will have empty for those not defined in dictionary

User · Answer

dic     female  1   male  0  w  female     w  female   replace dic    replace has as argument a dictionary in which you may change and do whatever you want or need

User · Answer

Alternatively there is the built-in function pd get dummies for these kinds of assignments   w  female     pd get dummies w  female   drop first   True    This gives you a data frame with two columns  one for each value that occurs in w  female    of which you drop the first  because you can infer it from the one that is left   The new column is automatically named as the string that you replaced    This is especially useful if you have categorical variables with more than two possible values  This function creates as many dummy variables needed to distinguish between all cases  Be careful then that you don t assign the entire data frame to a single column  but instead  if w  female   could be  male    female  or  neutral   do something like this   w   pd concat  w  pd get dummies w  female    drop first   True    axis   1   w drop  female   axis   1  inplace   True    Then you are left with two new columns giving you the dummy coding of  female  and you got rid of the column with the strings

User · Answer

You can edit a subset of a dataframe by using loc   df loc  lt row selection gt    lt column selection gt     In this case   w loc w female     female    female     0 w loc w female     female    female     1

User · Answer

Using Series map with Series fillna  If your column contains more strings than only female and male  Series map will fail in this case since it will return NaN for other values   That s why we have to chain it with fillna   Example why  map fails   df   pd DataFrame   female    male    female    female    male    other    other         female 0    male 1  female 2  female 3    male 4   other 5   other   df  female   map   female    1    male    0     0      0 1      1 2      1 3      0 4    NaN 5    NaN Name  female  dtype  object   For the correct method  we chain map with fillna  so we fill the NaN with values from the original column   df  female   map   female    1    male    0    fillna df  female     0        0 1        1 2        1 3        0 4    other 5    other Name  female  dtype  object

[python] Replacing column values in a pandas DataFrame

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