How to index the elements in a list for pandas?

Question

I have created a numpy array with the np.shape(sample_size, ), then I used pandas dataframe to display the data. I would like to ask you, how could I add subcolumn index for the list, for example: sample 1, sample 2, sample 3, etc ?

low = 0
high = 500
sample_size = 5

def get_numbers(low, high, sample_size):
    return random.sample(range(low, high), sample_size)

p_one = np.array(get_numbers(low, high, sample_size), dtype = int)
p_two = np.array(get_numbers(low, high, sample_size), dtype = int)
p_three = np.array(get_numbers(low, high, sample_size), dtype = int)
p_four = np.array(get_numbers(low, high, sample_size), dtype = int)
p_five = np.array(get_numbers(low, high, sample_size), dtype = int)

  for idn in range(0,n): #------------------n+1 for the last process step

        p = [p_one, p_two, p_three, p_four, p_five]

df_rawdata = pd.DataFrame(list(zip(p)),columns =['Processing'])

make example by code or text not image – Panda Kim Dec 23 '22 at 05:33 — Panda Kim, Dec 23 '22 at 05:33

Panda Kim · Accepted Answer · 2022-12-23T07:10:34.290

0

Example

we need minimal and reproducible example by code

df = pd.DataFrame([[[1, 2, 3]], [[4, 5, 6]]], index=['step1', 'step2'], columns=['process'])

df

        process
step1   [1, 2, 3]
step2   [4, 5, 6]

Code

first. expand list to columns

df1 = df['process'].apply(pd.Series).rename(columns=lambda x: f'sp {x+1}')

df1

        sp 1    sp 2    sp 3
step1   1       2       3
step2   4       5       6

second. make multi index

out = pd.concat([df1], keys=['process'], axis=1)

out

              process
        sp 1    sp 2    sp 3
step1   1       2       3
step2   4       5       6

Update

or use folowing example code:

df = pd.DataFrame([[[1, 2], [3, 4]], [[5, 6], [7, 8]]], index=['step1', 'step2'], columns=['process1', 'process2'])

df

      process1  process2
step1   [1, 2]  [3, 4]
step2   [5, 6]  [7, 8]

out = (df.stack()
       .apply(pd.Series).rename(columns=lambda x: f'sp {x+1}')
       .unstack().swaplevel(0, 1, axis=1).sort_index(axis=1))

out

        process1        process2
        sp 1    sp 2    sp 1    sp 2
step1   1       2       3       4
step2   5       6       7       8

edited Dec 23 '22 at 07:10

answered Dec 23 '22 at 05:48

Panda Kim

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Hi @Pandas Kim, thank you. Btw, now I am trying to combine all of them into 1 new dataframe, however the result is not as expected. df_rawdata = pd.DataFrame(list(zip(process_steps_n, p,c)),columns =['Steps','Processing','Cleaning']) df1 = df_rawdata['Processing'].apply(pd.Series).rename(columns=lambda x: f'sp {x+1}') df2 = df_rawdata['Cleaning'].apply(pd.Series).rename(columns=lambda x: f'sp {x+1}') outp = pd.concat([df1], keys=['Processing'], axis=1) df_rawdata2 = pd.DataFrame(list(zip(process_steps_n, outp,outc)),columns =['Steps','Processing','Cleaning']) – Nicholas TI Dec 23 '22 at 06:07
This always happens when questioner don't make example and expected output by code. – Panda Kim Dec 23 '22 at 06:11
@NicholasTI you can make example like me. at least you can type dataframe code manually. – Panda Kim Dec 23 '22 at 06:14
Hi @Pandas Kim, since I have limited characters on the comment section, I will make a new post and tag you, thank you :) – Nicholas TI Dec 23 '22 at 06:15
Hi @Panda Kim, I posted it here: https://stackoverflow.com/q/74897577/19260758 , thank you. – Nicholas TI Dec 23 '22 at 08:24
@NicholasTI did you see my update answer? i think that will solve it – Panda Kim Dec 23 '22 at 08:52

How to index the elements in a list for pandas?

1 Answers1