Python pandas insert list into a cell

Question

I have a list  abc  and a dataframe  df    abc     foo    bar   df       A  B 0  12  NaN 1  23  NaN   I want to insert the list into cell 1B  so I want this result       A  B 0  12  NaN 1  23    foo    bar     Ho can I do that   1  If I use this   df ix 1  B     abc   I get the following error message   ValueError  Must have equal len keys and value when setting with an iterable   because it tries to insert the list  that has two elements  into a row   column but not into a cell   2  If I use this   df ix 1  B      abc    then it inserts a list that has only one element that is the  abc  list      foo    bar        3  If I use this   df ix 1  B          join abc    then it inserts a string    foo  bar   but not a list   4  If I use this   df ix 1  B           join abc     then it inserts a list but it has only one element     foo  bar     but not two as I want     foo    bar       Thanks for help     EDIT  My new dataframe and the old list   abc     foo    bar   df2       A    B         C 0  12  NaN       bla  1  23  NaN   bla bla    Another dataframe   df3       A    B         C                    D 0  12  NaN       bla     item1    item2   1  23  NaN   bla bla          11  12  13    I want insert the  abc  list into df2 loc 1  B   and or df3 loc 1  B     If the dataframe has columns only with integer values and or NaN values and or list values then inserting a list into a cell works perfectly  If the dataframe has columns only with string values and or NaN values and or list values then inserting a list into a cell works perfectly  But if the dataframe has columns with integer and string values and other columns then the error message appears if I use this  df2 loc 1  B     abc or df3 loc 1  B     abc   Another dataframe   df4             A     B 0       bla   NaN 1   bla bla   NaN   These inserts work perfectly  df loc 1  B     abc or df4 loc 1  B     abc

User · Answer

Quick work around  Simply enclose the list within a new list  as done for col2 in the data frame below  The reason it works is that python takes the outer list  of lists  and converts it into a column as if it were containing normal scalar items  which is lists in our case and not normal scalars   mydict   col1   1 2 3   col2    1  4    2  5    3  6    data pd DataFrame mydict  data      col1     col2 0   1        1  4  1   2        2  5  2   3        3  6

User · Answer

df3 set value 1   B   abc  works for any dataframe  Take care of the data type of column  B   Eg  a list can not be inserted into a float column  at that case df  B     df  B   astype object  can help

User · Answer

I ve got a solution that s pretty simple to implement  Make a temporary class just to wrap the list object and later call the value from the class  Here s a practical example   Let s say you want to insert list object into the dataframe   df   pd DataFrame         a   1         a   2         a   3       df loc     b            1 2 4 2          1 2          4 5 6      This works  Because the list has the same length as the rows of the dataframe  df loc     c      1 2 4 5 3    This does not work     gt  gt  gt  ValueError  Must have equal len keys and value when setting with an iterable     To force pandas to have list as value in each cell  wrap the list with a temporary class   class Fake object       def   init   self  li obj           self obj   li obj  df loc     c     Fake  1 2 5 3 5 7      This works    df c   df c apply lambda x  x obj    Now extract the value from the class  This works     Creating a fake class to do this might look like a hassle but it can have some practical applications  For an example you can use this with apply when the return value is list  Pandas would normally refuse to insert list into a cell but if you use this method  you can force the insert

User · Answer

Since set value has been deprecated since version 0 21 0  you should now use at  It can insert a list into a cell without raising a ValueError as loc does  I think this is because at always refers to a single value  while loc can refer to values as well as rows and columns   df   pd DataFrame data   A    1  2  3    B     x    y    z      df at 1   B       m    n    df       A   B 0   1   x 1   2    m  n  2   3   z   You also need to make sure the column you are inserting into has dtype object  For example   gt  gt  gt  df   pd DataFrame data   A    1  2  3    B    1 2 3     gt  gt  gt  df dtypes A    int64 B    int64 dtype  object   gt  gt  gt  df at 1   B      1  2  3  ValueError  setting an array element with a sequence   gt  gt  gt  df  B     df  B   astype  object    gt  gt  gt  df at 1   B      1  2  3   gt  gt  gt  df    A          B 0  1          1 1  2   1  2  3  2  3          3

User · Answer

Also getting  ValueError  Must have equal len keys and value when setting with an iterable   using  at rather than  loc did not make any difference in my case  but enforcing the datatype of the dataframe column did the trick   df  B     df  B   astype object    Then I could set lists  numpy array and all sorts of things as single cell values in my dataframes

User · Answer

As mentionned in this post pandas  how to store a list in a dataframe   the dtypes in the dataframe may influence the results  as well as calling a dataframe or not to be assigned to

User · Answer

Pandas    0 21  set value has been deprecated   You can now use DataFrame at to set by label  and DataFrame iat to set by integer position   Setting Cell Values with at iat    Setup df   pd DataFrame   A    12  23    B      a    b      c    d      df      A       B 0  12   a  b  1  23   c  d   df dtypes  A     int64 B    object dtype  object   If you want to set a value in second row of the  B  to some new list  use DataFrane at   df at 1   B       m    n   df      A       B 0  12   a  b  1  23   m  n    You can also set by integer position using DataFrame iat  df iat 1  df columns get loc  B        m    n   df      A       B 0  12   a  b  1  23   m  n      What if I get ValueError  setting an array element with a sequence   I ll try to reproduce this with   df      A   B 0  12 NaN 1  23 NaN  df dtypes  A      int64 B    float64 dtype  object     df at 1   B       m    n     ValueError  setting an array element with a sequence    This is because of a your object is of float64 dtype  whereas lists are objects  so there s a mismatch there  What you would have to do in this situation is to convert the column to object first   df  B     df  B   astype object  df dtypes  A     int64 B    object dtype  object   Then  it works   df at 1   B       m    n   df      A       B 0  12     NaN 1  23   m  n      Possible  But Hacky  Even more wacky  I ve found you can hack through DataFrame loc to achieve something similar if you pass nested lists   df loc 1   B        m      n      o      p    df      A             B 0  12         a  b  1  23   m  n  o  p    You can read more about why this works here

[python] Python pandas insert list into a cell

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