dotnet/machinelearning · error · ArgumentException

Strings.BadColumnCast (formatted with column.DataType, typeo

Error message

Strings.BadColumnCast (formatted with column.DataType, typeof(Double))

What it means

DataFrameColumnCollection.GetDoubleColumn(name) only returns a column when it is exactly a DoubleDataFrameColumn. When a column exists under that name but has a different data type, the library throws ArgumentException with Strings.BadColumnCast, formatted with the actual column DataType and typeof(Double). It signals a type mismatch between the requested accessor and the stored column, not a missing column.

Source

Thrown at src/Microsoft.Data.Analysis/DataFrameColumnCollection.cs:342

            throw new ArgumentException(string.Format(Strings.BadColumnCast, column.DataType, typeof(Char)));
        }

        /// <summary>
        /// Gets the <see cref="DoubleDataFrameColumn"/> with the specified <paramref name="name"/>.
        /// </summary>
        /// <param name="name">The name of the column</param>
        /// <returns><see cref="DoubleDataFrameColumn"/>.</returns>
        /// <exception cref="ArgumentException">A column named <paramref name="name"/> cannot be found, or if the column's type doesn't match.</exception>
        public DoubleDataFrameColumn GetDoubleColumn(string name)
        {
            DataFrameColumn column = this[name];
            if (column is DoubleDataFrameColumn ret)
            {
                return ret;
            }

            throw new ArgumentException(string.Format(Strings.BadColumnCast, column.DataType, typeof(Double)));
        }

        /// <summary>
        /// Gets the <see cref="DecimalDataFrameColumn"/> with the specified <paramref name="name"/>.
        /// </summary>
        /// <param name="name">The name of the column</param>
        /// <returns><see cref="DecimalDataFrameColumn"/>.</returns>
        /// <exception cref="ArgumentException">A column named <paramref name="name"/> cannot be found, or if the column's type doesn't match.</exception>
        public DecimalDataFrameColumn GetDecimalColumn(string name)
        {
            DataFrameColumn column = this[name];
            if (column is DecimalDataFrameColumn ret)
            {
                return ret;
            }

            throw new ArgumentException(string.Format(Strings.BadColumnCast, column.DataType, typeof(Decimal)));
        }

View on GitHub (pinned to 7b76e69cf9)

Solutions

Check the column's actual type first: df.Columns["name"].DataType (or the column class name) and use the matching Get<ColumnType>Column accessor.
Convert the column to double before access: df.Columns["name"] = df.Columns["name"].Cast<double>(), then call GetDoubleColumn.
If the type can vary, access generically via df["name"] and inspect/convert values instead of using the typed accessor.
Fix upstream data ingestion (read options/schema) so the column is loaded as double.

Example fix

// before
var col = df.Columns.GetDoubleColumn("Price"); // throws if "Price" is float
// after
if (df.Columns["Price"].DataType == typeof(double))
{
    var col = df.Columns.GetDoubleColumn("Price");
}
else
{
    df.Columns["Price"] = df.Columns["Price"].Cast<double>();
    var col = df.Columns.GetDoubleColumn("Price");
}

Defensive patterns

Strategy: type-guard

Validate before calling

// before calling GetDoubleColumn
if (df.Columns.Contains("name") && df.Columns["name"].DataType != typeof(double))
    throw new InvalidOperationException($"Column 'name' is {df.Columns["name"].DataType}, expected double");

Type guard

static bool IsDoubleColumn(DataFrameColumn c) => c is DoubleDataFrameColumn;
// usage: if (df.Columns["name"] is DoubleDataFrameColumn dblCol) { ... }

Try / catch

try
{
    var col = df.Columns.GetDoubleColumn("name");
}
catch (ArgumentException ex) when (ex.Message.Contains("column"))
{
    // inspect df.Columns["name"].DataType, convert with .Cast<double>(), and retry
}

Prevention

Always check df.Columns[name].DataType before using a typed Get*Column accessor.
Prefer generic access via df["name"] plus explicit .Cast<double>() when column types come from external data.
Watch for float/decimal columns from numeric CSV or DB REAL/NUMERIC types; convert immediately after load.
Log the loaded schema after reading external data to catch inference surprises early.

When it happens

Trigger: Calling df.Columns.GetDoubleColumn("name") on a DataFrame whose column "name" exists but is not a DoubleDataFrameColumn (e.g. it was loaded as float, decimal, int, or string). The indexer this[name] succeeds, the `is DoubleDataFrameColumn` pattern fails, and the ArgumentException at src/Microsoft.Data.Analysis/DataFrameColumnCollection.cs:342 is thrown.

Common situations: CSV values inferred as float or Int64 instead of double; parquet/DB schemas with REAL or NUMERIC mapping to single/decimal; schema drift after a data source change; hardcoded column names pointing at a differently-typed column.

Understand the failure class

Background: Type mismatch errors: IllegalArgumentException, TypeError and type guards across 150 open-source libraries — this error's family across 150 libraries.

Related errors

AI-assisted analysis of dotnet/machinelearning@7b76e69cf9 (2026-09-11). Data as JSON: /api/errors/00fbb5fd780b8686. Report an issue: GitHub.