Indexing: loc and iloc¶

CupOfTea provides pandas-inspired position-based (iloc) and label-based (loc) indexing mechanisms.

🔢 Position-Based Indexing: `iloc`¶

Use iloc when referencing rows and columns by their zero-based integer indices.

Just like Python and pandas, negative integers count backwards from the end of the DataFrame:

// Access the very last row
Row lastRow = df.iloc(-1);

// Access second-to-last row
Row secondToLast = df.iloc(-2);

Retrieve a single cell by (rowIndex, columnIndex):

Object cell = df.iloc(0, 1);

Extract a 2D subset specifying (rowStart, rowEnd, colStart, colEnd):

// Extract rows 0..9 and columns 0..2
CupOfTea subTable = df.iloc().slice(0, 10, 0, 3);

Use loc when rows are indexed by a specific key column (e.g., ID, SKU, or UUID).

// Designate "user_id" as the index column
df.setIndex("user_id");

// Look up user with ID 4201
Row userRow = df.loc(4201);
System.out.println("User Name: " + userRow.getString("name"));

// df.loc(indexKey, columnName)
Object email = df.loc(4201, "email");