let’s say I have a data like:

parameter1 parameter2  2010 2011 2012
A          B           foo  foo  foo
           C           foo  foo  foo
           D           foo  foo  foo
M          N           bar  bar  bar
           O           bar  bar  bar

which exported to CSV would look something like this:

parameter1,parameter2,2010,2011,2012
A,B,foo,foo,foo
,C,foo,foo,foo
,D,foo,foo,foo
M,N,bar,bar,bar
,O,bar,bar,bar

when I try to read the csv like:

pd.read_csv("file.csv", index_col=[0,1])

I however get:

            2010  2011  2012
A      B    foo   foo   foo
NaN    C    foo   foo   foo
       D    foo   foo   foo
M      N    bar   bar   bar
NaN    O    bar   bar   bar

Is there a way to make Pandas understand that if the value haven’t been provided for a row Index as CSV it should treat it like the indexed hasn’t changed, instead of giving it NaN index?

What I would expect instead after reading csv:

            2010  2011  2012
A      B    foo   foo   foo
       C    foo   foo   foo
       D    foo   foo   foo
M      N    bar   bar   bar
       O    bar   bar   bar