pandas-dev/pandas · error · NameError

name {self.name!r} is not defined

Error message

name {self.name!r} is not defined

What it means

Raised by Term._resolve_name in pandas.core.computation.pytables when a left-hand-side identifier in an HDFStore 'where' expression is not present in env.queryables - the dict of indexable columns and data_columns the table exposes. It is raised as NameError and tells you the column does not exist or is not queryable in the table.

Source

Thrown at pandas/core/computation/pytables.py:91

class Term(ops.Term):
    env: PyTablesScope

    def __new__(cls, name, env, side=None, encoding=None):
        if isinstance(name, str):
            klass = cls
        else:
            klass = Constant
        return object.__new__(klass)

    def __init__(self, name, env: PyTablesScope, side=None, encoding=None) -> None:
        super().__init__(name, env, side=side, encoding=encoding)

    def _resolve_name(self):
        # must be a queryables
        if self.side == "left":
            # Note: The behavior of __new__ ensures that self.name is a str here
            if self.name not in self.env.queryables:
                raise NameError(f"name {self.name!r} is not defined")
            return self.name

        # resolve the rhs (and allow it to be None)
        try:
            return self.env.resolve(self.name, is_local=False)
        except UndefinedVariableError:
            return self.name

    # read-only property overwriting read/write property
    @property  # type: ignore[misc]
    def value(self):
        return self._value


class Constant(Term):
    def __init__(self, name, env: PyTablesScope, side=None, encoding=None) -> None:
        assert isinstance(env, PyTablesScope), type(env)
        super().__init__(name, env, side=side, encoding=encoding)

View on GitHub (pinned to 71959b8cb9)

Solutions

1. Write the DataFrame with the column declared queryable: store.put('df', df, format='table', data_columns=['colname']) or data_columns=True for all columns.
2. Verify the column is queryable: print(store.get_storer('df').non_index_axes) and check the data_columns list.
3. Fix typos by listing available columns: print(store.get_storer('df').data_columns).
4. If the column isn't queryable, read the whole frame and filter in pandas: df = store.get('df'); df[df['col'] > 5].

Example fix

# before
store.select('df', where='value > 5')   # NameError if 'value' is not a data_column

# after (declare at write time)
store.put('df', df, format='table', data_columns=['value'])
store.select('df', where='value > 5')
# or filter in pandas:
df = store.get('df')
df[df['value'] > 5]

def assert_queryable(store, key, column):
    storer = store.get_storer(key)
    queryable = list((storer.data_columns or [])) + (storer.index_axes or [])
    if column not in [getattr(a, 'name', None) for a in queryable]:
        raise NameError(f'{column!r} is not queryable; declare it as a data_column')

def is_queryable_column(store, key, column) -> bool:
    try:
        storer = store.get_storer(key)
        names = [getattr(a, 'name', None) for a in (storer.data_columns or [])]
        names += [getattr(a, 'name', None) for a in (storer.index_axes or [])]
        return column in names
    except Exception:
        return False

try:
    store.select('df', where=f'{col} > 5')
except NameError as e:
    if 'is not defined' in str(e):
        # read all and filter in pandas
        df = store.get('df')
        result = df[df[col] > 5]
    else:
        raise

When it happens

Trigger: store.select('df', where='nonexistent_col > 5'); pd.read_hdf(path, 'df', where='missing == 3'); querying a column that exists in the DataFrame but was not declared as a data_column when written to HDF5.

Common situations: Writing a DataFrame to HDF5 without data_columns=True (only the index is queryable by default); typos in column names; assuming all columns are queryable; schema drift between writer and reader (column renamed/removed).

Related errors

• arithmetic operations are not supported inside an HDFStore '
• Cannot compare {conv_val} of type {type(conv_val)} to {kind}
• query term is not valid [{self}]
• passing a filterable condition to a non-table indexer [{self
• unable to collapse Joint Filters

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/25a75872595cf839. Report an issue: GitHub.