How to covert row values into columns values?

[Pedroski55]

It is summer holiday.

Normally, I would be in Spain, in a beautiful mountain village, reading the paper in the square, having a coffee, later a beer, later a
walk to the top of the mountain.

But I'm stuck in China because of the virus!

So I took a look at pandas. Here is one way to solve your problem in pandas.

import pandas as pd

# open the file
csv_file = '/home/pedro/myPython/pandas/transpose_me.csv'
df = pd.read_csv(csv_file)

"""
>>> df
  col1  col2
0    a     1
1    a     2
2    b     3
3    b     4
4    c     5
5    c     6
>>>

"""
# get column 1 as a list
mylist = df['col1'].tolist()

# get rid of the duplicates
myset = set(mylist)
"""
>>> myset
{'a', 'c', 'b'}
"""
# change back to list
mylist = list(myset)
mylist.sort()

# make an empty dictionary
mydict = {mylist[i]:[] for i in range(len(mylist))}

# if there were more values in the row, need to change this
# then we would need another loop to go across the row
# len(df.columns) will tell you how many columns
# but if all the rows are different, well some values will just be NaN
for i in range(df.index.size):
    key = df.iat[i,0]
    if key in mylist:
        value = df.iat[i,1]
        mydict[key].append(value)

# make a new DataFrame
df2 = pd.DataFrame(mydict)
"""
>>> df2
   a  b  c
0  1  3  5
1  2  4  6
"""
# done
df3 = df2.T
"""
>>> df3
   0  1
a  1  2
b  3  4
c  5  6
>>>
"""