How to update values in a specific row in a Python Pandas DataFrame

Question

With the nice indexing methods in Pandas I have no problems extracting data in various ways  On the other hand I am still confused about how to change data in an existing DataFrame    In the following code I have two DataFrames and my goal is to update values in a specific row in the first df from values of the second df  How can I achieve this   import pandas as pd df   pd DataFrame   filename       test0 dat    test2 dat                                        m    12  13    n     None  None    df2   pd DataFrame   filename      test2 dat    n  16   index  0      this overwrites the first row but we want to update the second   df update df2     this does not update anything df loc df filename     test2 dat   update df2   print df    gives      filename   m     n 0  test0 dat  12  None 1  test2 dat  13  None   2 rows x 3 columns    but how can I achieve this       filename   m     n 0  test0 dat  12  None 1  test2 dat  13  16   2 rows x 3 columns

User · Answer

In SQL  I would have do it in one shot as update table1 set col1   new value where col1   old value  but in Python Pandas  we could just do this  data      ram   10     sam   15     tam   15    kids   pd DataFrame data  columns     Name    Age     kids  which will generate the following output       Name    Age 0   ram     10 1   sam     15 2   tam     15  now we can run  kids loc kids Age    15  Age     17 kids  which will show the following output Name    Age 0   ram     10 1   sam     17 2   tam     17  which should be equivalent to the following SQL update kids set age   17 where age   15

User · Answer

So first of all  pandas updates using the index  When an update command does not update anything  check both left-hand side and right-hand side  If you don t update the indices to follow your identification logic  you can do something along the lines of  gt  gt  gt  df loc df filename     test2 dat    n     df2 df2 filename     test2 dat   loc 0   n    gt  gt  gt  df Out 331        filename   m     n 0  test0 dat  12  None 1  test2 dat  13    16  If you want to do this for the whole table  I suggest a method I believe is superior to the previously mentioned ones  since your identifier is filename  set filename as your index  and then use update   as you wanted to  Both merge and the apply   approach contain unnecessary overhead   gt  gt  gt  df set index  filename   inplace True   gt  gt  gt  df2 set index  filename   inplace True   gt  gt  gt  df update df2   gt  gt  gt  df Out 292                m     n filename            test0 dat  12  None test2 dat  13    16

User · Answer

There are probably a few ways to do this  but one approach would be to merge the two dataframes together on the filename m column  then populate the column  n  from the right dataframe if a match was found   The n x  n y in the code refer to the left right dataframes in the merge   In 100    df   pd merge df1  df2  how  left   on   filename   m     In 101    df Out 101        filename   m   n x  n y 0  test0 dat  12  None  NaN 1  test2 dat  13  None   16  In 102    df  n     df  n y   fillna df  n x     In 103    df   df drop   n x   n y    axis 1   In 104    df Out 104        filename   m     n 0  test0 dat  12  None 1  test2 dat  13    16

User · Answer

If you have one large dataframe and only a few update values I would use apply like this   import pandas as pd  df   pd DataFrame   filename       test0 dat    test2 dat                                        m    12  13    n     None  None     data     filename      test2 dat    n  16   def update vals row  data data       if row filename    data  filename            row n   data  n       return row  df apply update vals  axis 1

User · Answer

I needed to update and add suffix to few rows of the dataframe on conditional basis based on the another column s value of the same dataframe - df with column Feature and Entity and need to update Entity based on specific feature type    df2  df1 df loc df Feature     dnb    Entity      duns     df loc df Feature     dnb   Entity

User · Answer

Update null elements with value in the same location in other  Combines a DataFrame with other DataFrame using func to element-wise combine columns  The row and column indexes of the resulting DataFrame will be the union of the two  df1   pd DataFrame   A    None  0    B    None  4    df2   pd DataFrame   A    1  1    B    3  3    df1 combine first df2       A    B 0  1 0  3 0 1  0 0  4 0  more information in this link

[python] How to update values in a specific row in a Python Pandas DataFrame?

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