[Python] CSVの読み込みエラー用の例外処理を定義する

import csv
try:
    with open('non_existent_file.csv', mode='r', encoding='utf-8') as file:
        reader = csv.reader(file)
        for row in reader:
            print(row)
except FileNotFoundError:
    print("指定されたファイルが見つかりません。ファイル名を確認してください。")

import csv
try:
    with open('invalid_format.csv', mode='r', encoding='utf-8') as file:
        reader = csv.reader(file)
        for row in reader:
            print(row)
except csv.Error as e:
    print(f"CSVファイルの形式が不正です: {e}")

import csv
try:
    with open('wrong_encoding.csv', mode='r', encoding='utf-8') as file:
        reader = csv.reader(file)
        for row in reader:
            print(row)
except UnicodeDecodeError:
    print("ファイルのエンコーディングが正しくありません。エンコーディングを確認してください。")

import csv
try:
    with open('data_type_mismatch.csv', mode='r', encoding='utf-8') as file:
        reader = csv.reader(file)
        for row in reader:
            # 例として、整数型に変換を試みる
            number = int(row[0])
            print(number)
except ValueError:
    print("データ型が不一致です。データを確認してください。")

import csv
def validate_row(row):
    # 例：年齢が0以上120以下であることを確認
    try:
        age = int(row['age'])
        if 0 <= age <= 120:
            return True
    except ValueError:
        pass
    return False
with open('data.csv', mode='r', encoding='utf-8') as file:
    reader = csv.DictReader(file)
    for row in reader:
        if validate_row(row):
            print("Valid row:", row)
        else:
            print("Invalid row:", row)

import csv
def fill_missing_values(row):
    # 例：欠損値をデフォルト値で埋める
    if not row['age']:
        row['age'] = '0'
    if not row['name']:
        row['name'] = 'Unknown'
    return row
with open('data.csv', mode='r', encoding='utf-8') as file:
    reader = csv.DictReader(file)
    for row in reader:
        row = fill_missing_values(row)
        print(row)

import csv
def convert_data_types(row):
    # 例：年齢を整数型に変換
    try:
        row['age'] = int(row['age'])
    except ValueError:
        row['age'] = 0  # デフォルト値
    return row
with open('data.csv', mode='r', encoding='utf-8') as file:
    reader = csv.DictReader(file)
    for row in reader:
        row = convert_data_types(row)
        print(row)

import csv
def detect_and_correct_invalid_data(row):
    # 例：年齢が不正な場合に修正
    try:
        age = int(row['age'])
        if age < 0 or age > 120:
            row['age'] = '0'  # 修正
    except ValueError:
        row['age'] = '0'  # 修正
    return row
with open('data.csv', mode='r', encoding='utf-8') as file:
    reader = csv.DictReader(file)
    for row in reader:
        row = detect_and_correct_invalid_data(row)
        print(row)

import pandas as pd
chunk_size = 1000  # 1回に読み込む行数
for chunk in pd.read_csv('large_data.csv', chunksize=chunk_size):
    # 各チャンクに対する処理
    print(chunk.head())

import pandas as pd
dtypes = {'column1': 'int32', 'column2': 'float32', 'column3': 'category'}
data = pd.read_csv('large_data.csv', dtype=dtypes)
print(data.info())

import pandas as pd
from concurrent.futures import ProcessPoolExecutor
def process_chunk(chunk):
    # 各チャンクに対する処理
    return chunk.sum()
chunk_size = 1000
results = []
with ProcessPoolExecutor() as executor:
    for chunk in pd.read_csv('large_data.csv', chunksize=chunk_size):
        future = executor.submit(process_chunk, chunk)
        results.append(future.result())
print(results)