Convert row to column header for Pandas DataFrame

Question

The data I have to work with is a bit messy   It has header names inside of its data  How can I choose a row from an existing pandas dataframe and make it  rename it to  a column header   I want to do something like   header   df df  old header name1       new header name1    df columns   header

User · Answer

This works  pandas v 0 19 2     df rename columns df iloc 0

User · Answer

In  21   df   pd DataFrame   1 2 3     foo   bar   baz     4 5 6     In  22   df Out 22         0    1    2 0    1    2    3 1  foo  bar  baz 2    4    5    6   Set the column labels to equal the values in the 2nd row  index location 1    In  23   df columns   df iloc 1    If the index has unique labels  you can drop the 2nd row using   In  24   df drop df index 1   Out 24    1 foo bar baz 0   1   2   3 2   4   5   6   If the index is not unique  you could use   In  133   df iloc pd RangeIndex len df   drop 1   Out 133    1 foo bar baz 0   1   2   3 2   4   5   6   Using df drop df index 1   removes all rows with the same label as the second row  Because non-unique indexes can lead to stumbling blocks  or potential bugs  like this  it s often better to take care that the index is unique  even though Pandas does not require it

User · Answer

To rename the header without reassign df  df rename columns df iloc 0   inplace   True   To drop the row without reassign df  df drop df index 0   inplace   True

User · Answer

You can specify the row index in the read csv or read html constructors via the header parameter which represents Row number s  to use as the column names  and the start of the data  This has the advantage of automatically dropping all the preceding rows which supposedly are junk   import pandas as pd from io import StringIO  In 1      csv      junk1  junk2  junk3  junk4  junk5     junk1  junk2  junk3  junk4  junk5     pears  apples  lemons  plums  other     40  50  61  72  85              df   pd read csv StringIO csv   header 2      print df   Out 1         pears   apples   lemons   plums   other     0     40       50       61      72      85

User · Answer

It would be easier to recreate the data frame  This would also interpret the columns types from scratch   headers   df iloc 0  new df    pd DataFrame df values 1    columns headers

[python] Convert row to column header for Pandas DataFrame,

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