Split pandas dataframe into groups of 20 and assign column value to each group-CodePudding

I have a df as follows.

TimeStamp,Value
 t1,akak
 t2,bb
 t3,vvv
 t5,ff
 t6,44
 t7,99
 t8,kfkkf
 t9,ff
 t10,oo

I want to split df into sizes of 2 rows and assign class as group number.

TimeStamp,Value, class
 t1,akak,c1
 t2,bb,c1
 t3,vvv,c2
 t4,ff,c2
 t5,44,c3
 t6,99,c3
 t7,kfkkf,c4
 t8,ff,c4
 t9,oo,c5
 t10,oo,c5

One approach is to iterate and do it one at a time. Was thinking of there is inbuilt way in pandas to do it

CodePudding user response：

You could do:

df['class'] = [i//2 for i in range(len(df))]

But this is a pretty limited answer; you might want to apply a certain value on your other columns to get the group ID, or you may have a specific label in mind to apply for the class column, in which case you could follow up with a map function on the series to turn those numbers into something else.

CodePudding user response：

You can use this to achieve what you want:

df["class"] = [f"c{(i // 2)   1}" for i in range(df.shape[0])]

CodePudding user response：

Another possible solution:

df['class'] = ['c'   str(int(x)) for x in np.repeat(np.arange(1, 1 len(df)/2), 2)]

Output:

  TimeStamp  Value class
0        t1   akak    c1
1        t2     bb    c1
2        t3    vvv    c2
3        t4     ff    c2
4        t5     ff    c3
5        t6     44    c3
6        t7     99    c4
7        t8  kfkkf    c4
8        t9     ff    c5
9       t10     oo    c5