Hi I am trying to split up a a large metadate file in Python. I started using pandas and wasn't able to figure it out. Right now it's a tab delimited file that looks something like:

```
id       count
MD1_G1   k123
MD1_G2   k34
MD2_G3   k5678
MD2_G4   k50633
MD4_G5   k100

```

First I wanted to try and split that first column into two. This is what I have so far:

```
df = pd.read_table('Table1.txt',names=["id","count"])
#This below was my attempt at trying to split that first column
df_tmp = pd.DataFrame(df.id.str.split('_',1).tolist(),columns=['id','descriptor'])

```

I managed to split that first column but I don't know how to do it while keeping the original `count` column. 

Once I split that column I wanted to try and iteratively go through and create a new tab delimited file for each unique ID. So in this example I want to get to a situation where I make 3 new files from the original that contain information only from the unique ID. So using the example, I want to get to a situation where I ultimately have 3 new files:

file 1: 

```
MD1  G1  k123
MD1  G2  k34

```

file 2:

```
MD2  G3   k5678
MD2  G4   k50633

```

file 3:

```
MD4  G5   k100

```

If anyone has any ideas please let me know!