如何在Python中对表格按指定列进行升序与降序排序（含PrettyTable实践示例）

Great question! You've already nailed ascending sorting with sortby and sort_key—let's break down a few straightforward ways to flip that to descending order for any column you want.

Method 1: Use the reverse Parameter (Simplest Approach) #

PrettyTable's get_string() method has a built-in reverse parameter that lets you flip the sorted order with zero extra logic. This is the fastest way to convert an ascending sort to descending.

First, a quick correction: In your original ascending code, you used row[0] for BirthYear—but BirthYear is the second column (0-indexed, so index 1). Fixing that, here's how to sort BirthYear in descending order:

from prettytable import from_csv

with open('test.txt', 'r') as open_file:
    table_file = from_csv(open_file)

# Sort BirthYear column in descending order
print(table_file.get_string(sortby='BirthYear', sort_key=lambda row: int(row[1]), reverse=True))

You can adapt this for any column easily. For example, sorting by Name in descending alphabetical order:

print(table_file.get_string(sortby='Name', sort_key=lambda row: row[0], reverse=True))

Method 2: Reverse the Sort Key Logic #

If you need more control over sorting behavior, adjust your sort_key lambda to return a reversed value. This works well for different data types:

• For numeric columns (like BirthYear), negate the value after converting it from string to integer:

  print(table_file.get_string(sortby='BirthYear', sort_key=lambda row: -int(row[1])))
  

  Negating larger numbers makes them "smaller" in the sort, which effectively gives a descending order.
• For string columns (like Job), you can use reversed string slices for simple descending sort, or locale-aware sorting for proper alphabetical order:

  # Simple reversed string sort for Job column
  print(table_file.get_string(sortby='Job', sort_key=lambda row: row[2][::-1]))
  
  # Locale-aware proper descending alphabetical sort (works for non-English too)
  import locale
  locale.setlocale(locale.LC_ALL, '')
  print(table_file.get_string(sortby='Job', sort_key=lambda row: locale.strxfrm(row[2]), reverse=True))
  

Method 3: Manually Sort Rows and Reconstruct the Table #

For full control over the sorting process (like adding pre-sort processing), extract the table rows, sort them with Python's built-in sorted() function, then build a new PrettyTable:

from prettytable import PrettyTable, from_csv

with open('test.txt', 'r') as open_file:
    table_file = from_csv(open_file)

# Define which column to sort by (e.g., "Job")
target_column = "Job"
column_index = table_file.field_names.index(target_column)

# Sort rows in descending order (adjust key logic based on column type)
sorted_rows = sorted(
    table_file.rows,
    key=lambda row: row[column_index],
    reverse=True
)

# Build new sorted table
sorted_table = PrettyTable(table_file.field_names)
for row in sorted_rows:
    sorted_table.add_row(row)

print(sorted_table)

This method keeps your original table intact, which is handy if you need to reference unsorted data later.

内容的提问来源于stack exchange，提问作者AbdulRahman