Print a list in nice columns

print_columns.py

# inspired by https://stackoverflow.com/questions/1524126/how-to-print-a-list-more-nicely

# needs refinement before I post as answer though. I'll update this at some point

from typing import Iterable, Literal
def print_columns(data:Iterable, columns:int=3, sep:str=" ", alignment:Literal[">","<","^"]=">"):
    """Prints a list of objects in columns.
    
    `data` should be an iterable object, such as a list. Each element of data will be converted to a string using the built in `str()`
    `sep` is a string used to separate the columns. defaults to `' '`
    `alignment` is a string used to align the columns. It can take the values `">"`, `"<"`, or `"^"` which mean right align, left align, centre align respectively. defaults to `'>'`.

    Example:
    >>> print_columns(["aaaa","b","c","d","e","f","g","h","i","j","kkk","l","m","n","o"], 3, "  ", "<")
    aaaa  b    c
    d     e    f
    g     h    i
    j     kkk  l
    m     n    o
    """
    data = [*data]
    if len(data)==0:
        print("")
        return
    data += [""]*(len(data) - len(data)//columns*columns)
    column_data = []
    column_lengths = []
    for i in range(columns):
        column_data.append(
            new_column := list(map(str, data[i::columns])),
        )
        column_lengths.append(max(len(item) for item in new_column))
    
    

    datas, lengths = zip(*zip(column_data,column_lengths))
    outstring=[]
    for data in zip(*datas):
        fmt_string = sep.join(f"{{:{alignment}{length}}}" for length in lengths)
        outstring.append(fmt_string.format(*data))
    print("\n".join(outstring))

print_columns2.py

import numpy as np
import pandas as pd

def print_columns(items, num_columns=6, sep="  ", read_down=True):
    ss = pd.concat([
            pd.Series(list(items)),
            pd.Series(
                [""] * int(np.ceil(len(items) / num_columns)*num_columns - len(items))
            )
        ],
        ignore_index=True
    )
    if read_down:
        ss = pd.DataFrame(ss.values.reshape((num_columns,-1))).transpose()
    else:
        ss = pd.DataFrame(ss.values.reshape((-1, num_columns)))
    widths = ss.apply(lambda item: item.str.len().max(), axis="rows")
    for column, width in zip(ss.columns, widths):
        ss[column] = ss[column].str.ljust(width,fillchar=" ")
    for index, row in ss.iterrows():
        print(sep.join(row))
print_columns_2(corpex.columns, num_columns=8, read_down=True)

# aaaa  e  i    m
# b     f  j    n
# c     g  kkk  o
# d     h  l