如何计算python中一个dataframe中不同元素的中位数

Question

I'm trying to calculate the average location of an animal in a certain area.

I have this kind of dataframe, where each 'N° Tag' is the specific individual, Lat is the latitude of the recorded position and Lon is the longitude of the recorded position:

N° Tag       Lat        Lon                        
     1      49.05567   -67.05242  
     4      49.05517   -67.05249
     1      49.05575   -67.05247
     2      49.05584   -67.05288
     4      49.05523   -67.04214
     2      49.05698   -67.05299
     1      49.05567   -67.05246
     1      49.05587   -67.05248
     4      49.05477   -67.05211

I would calculate the median position (median Lat and Lon) of each animal and add a column in the present dataframe with such value like this:

N° Tag       Lat        Lon        Median Lat   Median Lon                
     1      49.05567   -67.05242    49.05562    67.05562     
     4      49.05517   -67.05249    49.05612    67.05515     
     1      49.05575   -67.05247    49.05562    67.05562     
     2      49.05584   -67.05288    49.05571    67.05526     
     4      49.05523   -67.04214    49.05612    67.05515     
     2      49.05698   -67.05299    49.05571    67.05526     
     1      49.05567   -67.05246    49.05562    67.05562     
     1      49.05587   -67.05248    49.05562    67.05562     
     4      49.05477   -67.05211    49.05612    67.05515     

Thanks for the help!

Answer 1

Try using transform() :

df['median lon'] = df['lon'].groupby(df['n tag']).transform('median')