Extract table values

Deephaven tables have methods to extract values from tables into Python. Generally, this isn't necessary for Deephaven queries but may be useful for debugging and logging purposes, and other specific use cases such as using listeners.

to_numpy() (positional index access)

The recommended way to extract values from a table by positional index is using to_numpy. This converts table columns to NumPy arrays, which provide positional index access.

from deephaven import empty_table
from deephaven.numpy import to_numpy

result = empty_table(5).update(["Integers = i + 1"])

To extract a single value by positional index, convert the column to a NumPy array and access by index:

# Convert column to numpy array
integers_array = to_numpy(result, cols=["Integers"])

# Access value at positional index 1 (second row)
value = integers_array[1]
print(f"Value at index 1: {value}")

You can also use array slicing to extract multiple values:

# Get first three values
first_three = integers_array[0:3]
print(f"First three values: {first_three}")

Warning

to_numpy copies the entire table into memory. For large tables, consider limiting table size before converting.

Important

All columns passed to to_numpy must have the same data type. For mixed types, convert columns individually.

Iterate with for loops

For iteration, you can use standard Python for loops with NumPy arrays:

# Iterate over all values
for value in integers_array:
    print(value)

For multiple columns, convert each separately or use table operations:

from deephaven import empty_table
from deephaven.numpy import to_numpy

multi_col_table = empty_table(5).update(
    ["X = i + 1", "Y = (i + 1) * 10", "Z = (i % 2 == 0) ? `Even` : `Odd`"]
)

# Convert numeric columns
x_array = to_numpy(multi_col_table, cols=["X"])
y_array = to_numpy(multi_col_table, cols=["Y"])

# Iterate over multiple arrays together
for x_val, y_val in zip(x_array, y_array):
    print(f"X: {x_val}, Y: {y_val}")

Advanced: ColumnSource (row key access)

For advanced use cases, you can access the underlying Java ColumnSource via .j_object. This provides access by row key, not positional index.

from deephaven import empty_table

result = empty_table(5).update(["Integers = i + 1"])

# Access the underlying Java ColumnSource
column_source = result.j_object.getColumnSource("Integers")
print(column_source)

Important

ColumnSource methods use row keys, not positional indices. Row keys are internal identifiers that may not match positional indices, especially in filtered or modified tables.

For primitive columns, use type-specific methods:

# Get value for row key 2 using type-specific method
value = column_source.getInt(2)
print(f"Value for row key 2: {value}")

Type-specific ColumnSource methods:

  • getInt(rowKey) for int columns
  • getLong(rowKey) for long columns
  • getDouble(rowKey) for double columns
  • getFloat(rowKey) for float columns
  • get(rowKey) for object columns

Warning

Using .j_object directly accesses the Java layer and is not idiomatic Python. Use to_numpy() for most use cases.