使用open与csv.reader处理CSV文件的条件追加问题求助

Hey there! Let's break down how to solve both of your CSV handling needs cleanly and efficiently.

1. Better Way to Skip the First Two Rows #

Your current approach of calling next(reader) twice works perfectly fine for two rows, but if you ever need to skip more rows later (or just want a more scalable/readable method), using itertools.islice is a great alternative. It lets you slice the reader iterator directly to skip the first N rows in one line:

import csv
from itertools import islice

with open('gios-pjp-data.csv', 'r') as data:
    l = []
    reader = csv.reader(data, delimiter=';')
    # Skip first 2 rows (start iterating from index 2 onwards)
    reader = islice(reader, 2, None)
    # Rest of your processing code goes here

This is way cleaner than chaining multiple next() calls, especially if you end up needing to skip 5+ rows down the line.

2. Filter and Append Floats Greater Than 200 #

For your core requirement—extracting the first and third floating-point values (columns 2 and 4 in your CSV, which map to indexes 1 and 3 in zero-based counting) only when they're over 200—here's a straightforward implementation:

import csv
from itertools import islice

with open('gios-pjp-data.csv', 'r') as data:
    l = []
    reader = csv.reader(data, delimiter=';')
    # Skip the first two header rows
    reader = islice(reader, 2, None)
    
    for row in reader:
        # Convert the relevant columns to float values
        first_float = float(row[1])
        third_float = float(row[3])
        
        # Append each value to the list only if it meets the >200 condition
        if first_float > 200:
            l.append(first_float)
        if third_float > 200:
            l.append(third_float)

Quick Notes: #

• We use zero-based indexing here: row[0] is the date string, row[1] is your first float, row[2] the second, and row[3] the third.
• If you want to append both values as a pair (like a tuple (first_float, third_float)) instead of individual entries, just adjust the logic—for example, append the tuple if either value is over 200, or only if both are, depending on your exact needs.
• To handle edge cases (like rows with invalid non-float values), add a try-except block to avoid crashes:

  try:
      first_float = float(row[1])
      third_float = float(row[3])
  except ValueError:
      # Skip this row or log an error message
      continue
  

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