Filter numeric and specific value from excel column - Python

I have a column with mixed values as below:
Mixed Data - column name
100 socks
3467867327 - remove
94746723892 - remove
400 order
oils
essentials
b01232435 - remove
b0054543543543 - remove
garments
787 sales

I want to filter the column and remove the rows which are marked as remove above. I can achieve removing the string starting from "b0" but I am unable to apply filter to only numeric values. dtype is object of the columns. Below code does not work for me nor do I want to create a separate column to convert string to numeric.

pd.to_numeric(df['Mixed Data'],errors='coerce').min()

Note - the actual data is of huge count hence I need to a generic code and not specific code. Please help me.

import pandas as pd
df = pd.DataFrame.from_dict(
    {
        "Mixed Data": [
            "100 socks",
            "3467867327",
            "94746723892",
            "400 order",
            "oils",
            "essentials",
            "b01232435",
            "b0054543543543",
            "garments",
            "787 sales",
        ],
        "Some other column": [
            "a",
            "b",
            "c",
            "d",
            "e",
            "f",
            "g",
            "h",
            "i",
            "j",
        ],
    }
)
df = df[df["Mixed Data"].str.startswith("b0") == False][
    df["Mixed Data"].str.isnumeric() == False
]
print(df)