Get column index from column name in python pandas

Question

In R when you need to retrieve a column index based on the name of the column you could do  idx  lt - which names my data   my colum name    Is there a way to do the same with pandas dataframes

User · Answer

In case you want the column name from the column location (the other way around to the OP question), you can use:

>>> df.columns.get_values()[location]

Using @DSM Example:

>>> df = DataFrame({"pear": [1,2,3], "apple": [2,3,4], "orange": [3,4,5]})

>>> df.columns

Index(['apple', 'orange', 'pear'], dtype='object')

>>> df.columns.get_values()[1]

'orange'

Other ways:

df.iloc[:,1].name

df.columns[location] #(thanks to @roobie-nuby for pointing that out in comments.)

User · Answer

To modify DSM s answer a bit  get loc has some weird properties depending on the type of index in the current version of Pandas  1 1 5  so depending on your Index type you might get back an index  a mask  or a slice   This is somewhat frustrating for me because I don t want to modify the entire columns just to extract one variable s index  Much simpler is to avoid the function altogether  list df columns  index  pear    Very straightforward and probably fairly quick

User · Answer

how about this   df   DataFrame   pear    1 2 3    apple    2 3 4    orange    3 4 5    out   np argwhere df columns isin   apple    orange     ravel   print out   1 2

User · Answer

For returning multiple column indices  I recommend using the pandas Index method get indexer  if you have unique labels  df   pd DataFrame   quot pear quot    1  2  3    quot apple quot    2  3  4    quot orange quot    3  4  5    df columns get indexer   pear    apple      Out  array  0  1   dtype int64   If you have non-unique labels in the index  columns only support unique labels  get indexer for  It takes the same args as get indeder  df   pd DataFrame        quot pear quot    1  2  3    quot apple quot    2  3  4    quot orange quot    3  4  5         index  0  1  1   df index get indexer for  0  1     Out  array  0  1  2   dtype int64   Both methods also support non-exact indexing with  f i  for float values taking the nearest value with a tolerance  If two indices have the same distance to the specified label or are duplicates  the index with the larger index value is selected  df   pd DataFrame        quot pear quot    1  2  3    quot apple quot    2  3  4    quot orange quot    3  4  5        index  0   9  1 1   df index get indexer  0  1     array   0  -1   dtype int64

User · Answer

DSM s solution works  but if you wanted a direct equivalent to which you could do  df columns    name  nonzero

User · Answer

Sure  you can use  get loc     In  45   df   DataFrame   pear    1 2 3    apple    2 3 4    orange    3 4 5     In  46   df columns Out 46   Index  apple  orange  pear   dtype object   In  47   df columns get loc  pear   Out 47   2   although to be honest I don t often need this myself   Usually access by name does what I want it to  df  pear    df   apple    orange     or maybe df columns isin   orange    pear      although I can definitely see cases where you d want the index number

User · Answer

When you might be looking to find multiple column matches  a vectorized solution using searchsorted method could be used  Thus  with df as the dataframe and query cols as the column names to be searched for  an implementation would be -  def column index df  query cols       cols   df columns values     sidx   np argsort cols      return sidx np searchsorted cols query cols sorter sidx     Sample run -  In  162   df Out 162       apple  banana  pear  orange  peach 0      8       3     4       4      2 1      4       4     3       0      1 2      1       2     6       8      1  In  163   column index df    peach    banana    apple    Out 163   array  4  1  0

User · Answer

Here is a solution through list comprehension  cols is the list of columns to get index for    df columns get loc c  for c in cols if c in df

[python] Get column index from column name in python pandas

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