Select Pandas rows based on list index

Question

I have a dataframe df       20060930  10 103       NaN     10 103   7 981    20061231  15 915       NaN     15 915  12 686    20070331   3 196       NaN      3 196   2 710    20070630   7 907       NaN      7 907   6 459   Then I want to select rows with certain sequence numbers which indicated in a list  suppose here is  1 3   then left      20061231  15 915       NaN     15 915  12 686    20070630   7 907       NaN      7 907   6 459   How or what function can do that

User · Answer

There are many ways of solving this problem  and the ones listed above are the most commonly used ways of achieving the solution  I want to add two more ways  just in case someone is looking for an alternative  index list    1 3   df take pos    or  df query  index in  index list

User · Answer

ind list    1  3  df ix ind list   should do the trick  When I index with data frames I always use the  ix   method  Its so much easier and more flexible    UPDATE This is no longer the accepted method for indexing  The ix method is  deprecated  Use  iloc for integer based indexing and  loc for label based indexing

User · Answer

For large datasets  it is memory efficient to read only selected rows via the skiprows parameter  Example pred   lambda x  x not in  1  3  pd read csv  quot data csv quot   skiprows pred  index col 0  names       This will now return a DataFrame from a file that skips all rows except 1 and 3   Details From the docs   skiprows   list-like or integer or callable  default None     If callable  the callable function will be evaluated against the row indices  returning True if the row should be skipped and False otherwise  An example of a valid callable argument would be lambda x  x in  0  2   This feature works in version pandas 0 20 0    See also the corresponding issue and a related post

User · Answer

you can also use iloc   df iloc  1 3       This will not work if the indexes in your dataframe do not correspond to the order of the rows due to prior computations  In that case use    df index isin  1 3         as suggested in other responses

User · Answer

Another way  although it is a longer code  but it is faster than the above codes  Check it using  timeit function  df df index isin  1 3     PS  You figure out the reason

[python] Select Pandas rows based on list index

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