diff --git a/src/jsonchain/tables.py b/src/jsonchain/tables.py
new file mode 100644
index 0000000..7c4b7f8
--- /dev/null
+++ b/src/jsonchain/tables.py
@@ -0,0 +1,154 @@
+from typing import Optional
+import csv
+import pathlib
+from openpyxl import load_workbook
+
+def load_csv(
+    csv_file: str | pathlib.Path,
+) -> list[list[str | float]]:
+    """
+    Reads the csv table at 'csv_file'
+
+    str values that are numeric are converted to ints or floats,
+    if possible.
+    """
+    with open(csv_file, 'r') as file:
+        return to_numeric(list(csv.reader(file)))
+
+
+def load_excel_sheet(
+    wb_file: str | pathlib.Path,
+    sheet_indexes: Optional[int | list[int]] = None,
+) -> list[list[str | float]] | dict[str, list[list[str | float]]]:
+    """
+    Reads the 
+    """
+    wb = load_workbook(wb_file)
+    if isinstance(sheet_indexes, int):
+        ws = wb.worksheets[sheet_indexes]
+        return table_cell_values(ws)
+    else:
+        wb_acc = {}
+        for ws in wb.worksheets:
+            wb_acc.update({ws.title: table_cell_values(ws)})
+        return wb_acc
+
+
+def table_cell_values(
+    ws: "openpyxl.Worksheet",
+) -> list[list[str | float]]:
+    """
+    Extract cell values from a worksheet by row
+    """
+    table_acc = [] # outer_acc
+    for row in ws.iter_rows(): # Use this method to extract data row-wise
+        row_acc = [] # inner_acc
+        for cell in row:
+            row_acc.append(cell.value)
+        table_acc.append(row_acc)
+    return table_acc
+
+
+def to_numeric(table: list[list[str]]) -> list[list[str | float]]:
+    """
+    Converts the cells in 'table' to ints and floats, if possible.
+    """
+    table_acc = []
+    for row in table:
+        row_acc = []
+        for cell in row:
+            try:
+                cell = int(cell)
+            except:
+                try:  
+                    cell = float(cell)
+                except:
+                    cell = cell
+            row_acc.append(cell)
+        table_acc.append(row)
+    return table_acc
+
+
+def transpose(table: list[list[str | float]]) -> list[tuple[str | float]]:
+    """
+    Returns 'table' transposed (rows become columns, columns become rows)
+    """
+    return list(zip(*table))
+
+
+def drop_rows(table: list[list[str | float]], rows_to_drop: int | list[int]) -> list[list[str | float]]:
+    """
+    Returns 'table' but with the row indexes in 'rows_to_drop' omitted.
+    """
+    if isinstance(rows_to_drop, int):
+        rows_to_drop = [rows_to_drop]
+    table_acc = []
+    for idx, row in enumerate(table):
+        if idx not in rows_to_drop:
+            table_acc.append(row)
+    return table_acc
+
+
+def drop_columns(table: list[list[str | float]], cols_to_drop: int | list[int]) -> list[tuple[str | float]]:
+    """
+    Returns 'table' but with the col indexes in 'cols_to_drop' omitted.
+    """
+    table_cols = transpose(table)
+    if isinstance(cols_to_drop, int):
+        cols_to_drop = [cols_to_drop]
+    table_acc = []
+    for idx, col in enumerate(table_cols):
+        if idx not in cols_to_drop:
+            table_acc.append(col)
+    return transpose(table_acc)
+
+
+def filter_table(
+    table: list[list[str | float]], 
+    filter_col: int, 
+    filter_rule: callable
+):
+    """
+    Filters the based on the values in 'filter_col'.
+    """
+    filtered_table = []
+    for row in table[1:]: # Skip the header row
+        if filter_rule(row[filter_col]):
+            filtered_table.append(row)
+    # Put header row back on
+    filtered_table = [table[0]] + filtered_table
+    return filtered_table
+
+
+def create_tree_table(
+    table: list[list[str | float]],
+    ordered_tree_indexes: list[int],
+) -> dict:
+    """
+    Returns a nested dictionary that has a depth equal to the length of 'ordered_tree_indexes'.
+
+    'ordered_tree_indexes' are column indexes in the table that are to be used to index the resulting
+        tree. 
+
+    Any column indexes that are not in 'ordered_tree_indexes' will become part of the "leaf dictionary"
+    at the end of the nested dictionary path.
+    """
+    tree_acc = {}
+    non_tree_indexes = [idx for idx in range(len(table[0])) if idx not in ordered_tree_indexes]
+    header_row = table[0]
+    for row in table[1:]:
+        tree_branch = None
+        for tree_index in ordered_tree_indexes:
+            if tree_branch is None:
+                tree_acc.setdefault(row[tree_index], {})
+                tree_branch = tree_acc[row[tree_index]]
+            else:
+                tree_branch.setdefault(row[tree_index], {})
+                tree_branch = tree_branch[row[tree_index]]
+                
+        tree_leaves = {}
+        for idx in non_tree_indexes:
+            tree_leaves.update({header_row[idx]: row[idx]})
+        tree_branch.update(tree_leaves)
+    return tree_acc 
+    
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