How to reformat horizontal csv to a more vertical format

Question

The above CSV is just a small snippet of the data, there are lots of data entries.

A simple transpose will not work

I need to get into the following format:

I have tried some methods with pandas and transpose but cannot figure it out. The CSV could be potentially thousands of lines long

Answer 1

You read the data by using pandas, and try the following code

df = pd.read_csv('name_file.csv')

(df.assign(idx=df.groupby('Entry').cumcount()).melt(['Entry', 'idx'])
   .pivot(index=['idx', 'variable'], columns='Entry', values='value')
   .droplevel('idx').rename_axis(index=None, columns=None)
)

Answer 2

You can use:

#if entry is index, remove "set_index('Entry')" field.
final=pd.concat([df[:4].set_index('Entry').T,df[4:].set_index('Entry').T])

Output :

|          | 0        | 1        | 2   |   3 |
|:---------|:---------|:---------|:----|----:|
| Blue     | 3/20/20  | 3:09 PM  | O   |  12 |
| Red      | 3/20/20  | 9:13 PM  | C   |   0 |
| Purple   | 11/26/22 | 3:09 PM  | O   |  34 |
| Green    | 3/20/20  | 3:09 PM  | O   |  24 |
| Black    | 3/20/20  | 3:09 PM  | O   | 133 |
| Orange   | 3/20/20  | 3:09 PM  | O   |  72 |
| Yellow   | 3/20/20  | 3:09 PM  | O   |   2 |
| Gold     | 3/20/20  | 3:00 PM  | O   |  13 |
| White    | 3/20/20  | 3:00 PM  | O   |  31 |
| Silver   | 3/20/20  | 8:49 PM  | O   |  43 |
| Bronze   | 3/20/20  | 2:22 PM  | C   |  13 |
| Platinum | 3/20/20  | 3:00 PM  | O   |  59 |
| Titanium | 3/20/20  | 3:00 PM  | O   |  63 |
| Blue     | 5/1/20   | 9:13 PM  | O   |  23 |
| Red      | 5/1/20   | 9:13 PM  | C   |   0 |
| Purple   | 5/1/20   | 5:24 PM  | O   |  45 |
| Green    | 5/1/20   | 12:09 PM | O   |  67 |
| Black    | 5/1/20   | 3:09 PM  | O   |  56 |
| Orange   | 5/1/20   | 3:09 PM  | O   | 754 |
| Yellow   | 5/1/20   | 3:09 PM  | O   |  23 |
| Gold     | 5/1/20   | 3:00 PM  | O   |  56 |
| White    | 5/1/20   | 3:00 PM  | O   | 121 |
| Silver   | 5/1/20   | 8:49 PM  | O   |  92 |
| Bronze   | 5/1/20   | 2:22 PM  | C   |  13 |
| Platinum | 5/1/20   | 3:00 PM  | O   |  59 |
| Titanium | 5/1/20   | 3:00 PM  | O   |  63 |

Answer 3

@Bushmaster's solution works fine. Another option is to transpose the column, then pivot with pivot_longer from pyjanitor :

# pip install pyjanitor
import janitor
import pandas as pd

df = pd.read_csv('Downloads/original.csv')

(df
.astype({"Entry":str})
.set_index('Entry')
.T
.pivot_longer(
    index=None, 
    ignore_index=False,
    names_to = '.value', 
    names_pattern='(.)')
)
                 0         1  2    3
Blue       3/20/20   3:09 PM  O   12
Red        3/20/20   9:13 PM  C    0
Purple    11/26/22   3:09 PM  O   34
Green      3/20/20   3:09 PM  O   24
Black      3/20/20   3:09 PM  O  133
Orange     3/20/20   3:09 PM  O   72
Yellow     3/20/20   3:09 PM  O    2
Gold       3/20/20   3:00 PM  O   13
White      3/20/20   3:00 PM  O   31
Silver     3/20/20   8:49 PM  O   43
Bronze     3/20/20   2:22 PM  C   13
Platinum   3/20/20   3:00 PM  O   59
Titanium   3/20/20   3:00 PM  O   63
Blue        5/1/20   9:13 PM  O   23
Red         5/1/20   9:13 PM  C    0
Purple      5/1/20   5:24 PM  O   45
Green       5/1/20  12:09 PM  O   67
Black       5/1/20   3:09 PM  O   56
Orange      5/1/20   3:09 PM  O  754
Yellow      5/1/20   3:09 PM  O   23
Gold        5/1/20   3:00 PM  O   56
White       5/1/20   3:00 PM  O  121
Silver      5/1/20   8:49 PM  O   92
Bronze      5/1/20   2:22 PM  C   13
Platinum    5/1/20   3:00 PM  O   59
Titanium    5/1/20   3:00 PM  O   63