恭喜你！

使用 Java 進行資料清理

Dennis Lee

Software Engineer

資料清理之旅

// From assessing quality
DescriptiveStatistics stats = new DescriptiveStatistics(values);
System.out.println("Mean: " + stats.getMean());


// To transforming strings
String clean = text.trim().toLowerCase();


// To validating ranges
boolean isValid = Range.between(0, 100).contains(value);


// To cleaning tables
Table cleaned = data.where(sales.isGreaterThan(1000));

評估資料品質

劣質資料會導致錯誤決策
評估資料品質：檢查離群值、遺漏值、錯誤型別

// Check statistics
double mean = stats.getMean();


// Detect nulls
boolean isMissing = Optional.ofNullable(value).isEmpty();


// Verify types
boolean isValidDate = LocalDate.parse(dateStr, formatter);

一致地轉換資料

格式不一致會影響分析正確性
清理字串；標準化類別與日期

// Normalize strings (e.g., remove non-letters)
String cleaned = dirtyName.replaceAll("[^a-zA-Z\\s]", "");


// Standardize categories
String standard = categoryMap.getOrDefault(value, "Other");


// Convert dates
LocalDateTime datetime = LocalDateTime.parse(dateStr, formatter);

驗證資料完整性

在資料進入系統前就把關
依商業規則檢查數值範圍與格式

// Check ranges
boolean inRange = Range.between(min, max).contains(value);


// Validate patterns
boolean matches = Pattern.matches(pattern, text);


// Enforce constraints
Set<ConstraintViolation<Data>> violations = validator.validate(data);

清理表格資料

for (String colName : data.columnNames()) {
    // Check missing values 
    System.out.println(data.column(colName).countMissing());
}


StringColumn cleaned = names.map(String::toLowerCase)   // Clean text
        .setName("Clean_Names");                        // Name new column


Table summary = data
        .where(sales.isGreaterThan(1000))               // Filter rows
        .summarize("Sales", mean)                       // Aggregate data
        .by("Category");                                // Group results

資源

準備好開始清理

使用 Java 進行資料清理