Python pandas fill a dataframe row by row

Question

The simple task of adding a row to a pandas DataFrame object seems to be hard to accomplish  There are 3 stackoverflow questions relating to this  none of which give a working answer   Here is what I m trying to do  I have a DataFrame of which I already know the shape as well as the names of the rows and columns    gt  gt  gt  df   pandas DataFrame columns   a   b   c   d    index   x   y   z     gt  gt  gt  df      a    b    c    d x  NaN  NaN  NaN  NaN y  NaN  NaN  NaN  NaN z  NaN  NaN  NaN  NaN   Now  I have a function to compute the values of the rows iteratively  How can I fill in one of the rows with either a dictionary or a pandas Series   Here are various attempts that have failed    gt  gt  gt  y     a  1   b  5   c  2   d  3    gt  gt  gt  df  y     y AssertionError  Length of values does not match length of index   Apparently it tried to add a column instead of a row    gt  gt  gt  y     a  1   b  5   c  2   d  3    gt  gt  gt  df join y  AttributeError   builtin function or method  object has no attribute  is unique    Very uninformative error message    gt  gt  gt  y     a  1   b  5   c  2   d  3    gt  gt  gt  df set value index  y   value y  TypeError  set value   takes exactly 4 arguments  3 given    Apparently that is only for setting individual values in the dataframe    gt  gt  gt  y     a  1   b  5   c  2   d  3    gt  gt  gt  df append y  Exception  Can only append a Series if ignore index True   Well  I don t want to ignore the index  otherwise here is the result    gt  gt  gt  df append y  ignore index True       a    b    c    d 0  NaN  NaN  NaN  NaN 1  NaN  NaN  NaN  NaN 2  NaN  NaN  NaN  NaN 3    1    5    2    3   It did align the column names with the values  but lost the row labels    gt  gt  gt  y     a  1   b  5   c  2   d  3    gt  gt  gt  df ix  y     y  gt  gt  gt  df                                   a                                 b    x                               NaN                               NaN y    a   1   c   2   b   5   d   3     a   1   c   2   b   5   d   3  z                               NaN                               NaN                                    c                                 d x                               NaN                               NaN y    a   1   c   2   b   5   d   3     a   1   c   2   b   5   d   3  z                               NaN                               NaN   That also failed miserably   So how do you do it

User · Answer

My approach was  but I can t guarantee that this is the fastest solution   df   pd DataFrame columns   firstname    lastname    df   df append         firstname    John         lastname     Johny           ignore index True

User · Answer

This is a simpler version  import pandas as pd df   pd DataFrame columns   col1    col2    col3    for i in range 5      df loc i       lt some value for first gt     lt some value for second gt     lt some value for third gt

User · Answer

df  y   will set a column  since you want to set a row  use  loc  Note that  ix is equivalent here  yours failed because you tried to assign a dictionary to each element of the row y probably not what you want  converting to a Series tells pandas that you want to align the input  for example you then don t have to to specify all of the elements   In  7   df   pandas DataFrame columns   a   b   c   d    index   x   y   z     In  8   df loc  y     pandas Series   a  1   b  5   c  2   d  3    In  9   df Out 9         a    b    c    d x  NaN  NaN  NaN  NaN y    1    5    2    3 z  NaN  NaN  NaN  NaN

User · Answer

If your input rows are lists rather than dictionaries  then the following is a simple solution   import pandas as pd list of lists      list of lists append  1 2 3   list of lists append  4 5 6    pd DataFrame list of lists  columns   A    B    C         A  B  C   0  1  2  3   1  4  5  6

[python] Python pandas: fill a dataframe row by row

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