Menu
I am trying to re-index a pandas DataFrame object, like so,
From: a b c 0 1 2 3 1 10 11 12 2 20 21 22 To : b c 1 2 3 10 11 12 20 21 22 I am going about this as shown below and am getting the wrong answer. Any clues on how to do this?
>>> col = ['a','b','c'] >>> data = DataFrame([[1,2,3],[10,11,12],[20,21,22]],columns=col) >>> data a b c 0 1 2 3 1 10 11 12 2 20 21 22 >>> idx2 = data.a.values >>> idx2 array([ 1, 10, 20], dtype=int64) >>> data2 = DataFrame(data,index=idx2,columns=col[1:]) >>> data2 b c 1 11 12 10 NaN NaN 20 NaN NaN Any idea why this is happening?
299
To change the index values we need to use the set_index method which is available in pandas allows specifying the indexes. where, inplace parameter accepts True or False, which specifies that change in index is permanent or temporary. True indicates that change is Permanent.
To set the DataFrame index using existing columns or arrays in Pandas, use the set_index() method. The set_index() function sets the DataFrame index using existing columns. The index can replace the existing index or expand on it.
If you want to keep the original index as a column, use reset_index() to reassign the index to a sequential number starting from 0 . You can change the index to a different column by using set_index() after reset_index() .
One can reindex a single column or multiple columns by using reindex() method and by specifying the axis we want to reindex. Default values in the new index that are not present in the dataframe are assigned NaN.
If you don't want 'a' in the index
In :
col = ['a','b','c'] data = DataFrame([[1,2,3],[10,11,12],[20,21,22]],columns=col) data Out:
a b c 0 1 2 3 1 10 11 12 2 20 21 22 In :
data2 = data.set_index('a') Out:
b c a 1 2 3 10 11 12 20 21 22 In :
data2.index.name = None Out:
b c 1 2 3 10 11 12 20 21 22 Why don't you simply use set_index method?
In : col = ['a','b','c'] In : data = DataFrame([[1,2,3],[10,11,12],[20,21,22]],columns=col) In : data Out: a b c 0 1 2 3 1 10 11 12 2 20 21 22 In : data2 = data.set_index('a') In : data2 Out: b c a 1 2 3 10 11 12 20 21 22 If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
