Is there a Python Function for this?

user_15040738 0
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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: enter image description here

to :enter image description here

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.

pandas python
2 Answers

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.
user_21069340

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
user_100359850
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