Python 3读取文本文件前5列并提取温度相关数据的技术问询

Here's a practical approach to solve this problem. The core idea is to filter out non-data lines (like separators or headers) and then pull the first 5 columns from valid entries.

Approach #

• Skip irrelevant lines: We'll ignore lines that are full of dashes (the separator) or start with header text like "Day" (since those don't contain your target temperature/date data).
• Extract valid columns: For lines that start with a date format (e.g., MM/DD), split the line into columns using whitespace and grab the first 5 entries.
• Optional processing: You can extend this to immediately track the lowest temperature and its corresponding date/year right in the loop.

Example Code #

def get_valid_data(file_path):
    valid_entries = []
    # Track the lowest temperature and its details (customize as needed)
    lowest_temp = None
    lowest_temp_details = None

    with open(file_path, 'r') as file:
        for line in file:
            stripped_line = line.strip()
            # Skip empty lines
            if not stripped_line:
                continue
            # Skip separator lines (all dashes)
            if stripped_line.startswith('-'):
                continue
            # Skip header lines
            if stripped_line.startswith('Day'):
                continue
            
            columns = stripped_line.split()
            # Make sure we have at least 5 columns to avoid errors
            if len(columns) >= 5:
                first_five = columns[:5]
                valid_entries.append(first_five)
                
                # Example: Track the lowest temperature (assuming 4th column is temp, index 3)
                current_temp = int(first_five[3])
                if lowest_temp is None or current_temp < lowest_temp:
                    lowest_temp = current_temp
                    lowest_temp_details = {
                        'date': first_five[0],
                        'year': first_five[2],
                        'temp': current_temp
                    }
    
    print("Lowest record temperature details:", lowest_temp_details)
    return valid_entries

# Replace with your actual file path
file_path = 'weather_data.txt'
data = get_valid_data(file_path)

# Print all valid first 5 column entries
print("\nValid first 5 column entries:")
for entry in data:
    print(entry)

Customization Tips #

• If your irrelevant lines have different patterns (e.g., other header keywords), adjust the skip conditions (like changing startswith('Day') to match your actual header text).
• Double-check the column indices for temperature/year based on your real data structure — in the example, we assumed the 4th column (index 3) is the temperature and the 3rd column (index 2) is the year, but you might need to tweak these.

内容的提问来源于stack exchange，提问作者user9572081