Is there a Python Function for this?

Question

Ok, So I manually wrote out a function to do this, but I am wondering if there is a built in python/pandas/numpy/... function for this. Essentially what I want is

data_col = data.loc[data['col3'] == 'a']
data_final = data_col['col2']

But I want it for all of the values of col3. So it goes from:

to:

Note how the values from col1 are not present. If there is no function that you can think of that does something like this, don't worry about making one. I already finished it and it suited my needs. Just curious, I haven't finished all of my courses in school yet so I am not super familiar with all of the functions.

Answer 1

Code

df = df.pivot_table(
    'col2', columns='col3', aggfunc=(lambda x:x.to_list())
).apply(pd.Series.explode).rename_axis(None, axis=1).reset_index(drop=True))

Output

    a   b   c   d   e
0   6   7   8   9   10
1   10  9   8   7   6

Explanation

1. By using pivot table we can list all elements of col2 based on groups of col3 and then we can explode the list.
2. rename_axis and reset_index are used at the end are to convert the index as per requirement.

Answer 2

Try:

for v in df["col3"].unique():
    m = df["col3"] == v
    df.loc[m, "tmp"] = range(m.sum())

df = df.pivot(index="tmp", columns="col3", values="col2").rename_axis("")
print(df)

Prints:

col3   a  b  c  d   e
                     
0.0    6  7  8  9  10
1.0   10  9  8  7   6