Converge columns in dataframe to single column in specific order - python-3.x

Question

Python newb here, I have two columns in a data frame, we'll call them dat1 and dat2
dat1 dat2
0 123 20
1 456 30
2 789 10
3 123 10
4 456 20
5 789 30
I need to convert that into a single column like so:
10
789
123
20
123
456
30
456
789
or in terms of columns, [dat2,dat1,dat1,dat2,dat1,dat1,dat2,dat1,dat1]
I made up this terrible code:
unique = dp['dat2'].unique()
for each in unique:
mylist.append(each)
for x in dp:
mylist.append(dp[dp['dat2'] == each])
and i get the output as below
20
dat1 dat2
0 123 20
4 456 20
dat1 dat2
0 123 20
4 456 20
30
dat1 dat2
1 456 30
5 789 30
dat1 dat2
1 456 30
5 789 30
10
dat1 dat2
2 789 10
3 123 10
dat1 dat2
2 789 10
3 123 10
I'm basically trying to replicate the function of the pivot table in excel. Any help would be really appreciated.
Thanks

Answer 1

# sort the values by the second column
dp = dp.sort_values(by='dat2')
# create a list which will collect the results
my_data = []
# loop over the 2nd unique columns values
for d2 in dp.dat2.unique():
# insert the data into the list
my_data.append(d2)
# grep the dat1 data from the table, where dat2 == d2
for i in dp.dat1[dp.dat2 == d2]:
my_data.append(i)
my_data
[10, 789, 123, 20, 123, 456, 30, 456, 789]

Answer 2

using pd.concat you can concat the dataframe data
import pandas as pd
df={'id1':[11,22,33],'id2':[77,88,99]}
df=pd.DataFrame(df)
print(pd.concat([df['id1'],df['id2']]))

Answer 3

Since it looks like you are grouping the values based on column dat2 and adding elements from dat1 after each dat2 element, I would use pd.groupby
import pandas as pd
dat1 = [123,456,789,123,456,789]
dat2 = [20,30,10,10,20,30]
df = pd.DataFrame(list(zip(dat1, dat2)), columns=['dat1', 'dat2'])
grouped = df.groupby(['dat2']).agg({'dat1':list}).reset_index()
dict_list = grouped.to_dict('records')
new_data_list = []
for single_dict in dict_list:
new_data_list.append(single_dict['dat2'])
new_data_list += single_dict['dat1']
print(new_data_list)
result:
[10, 789, 123, 20, 123, 456, 30, 456, 789]