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To sort the rows in a dataframe in ascending order based on a column, taking into account the entire value of the number, you can use the sort_values() method of a pandas dataframe and set the parameter "key" to a lambda function that converts the columns to a numeric type. The code snippet below demonstrates how to do this:

import pandas as pd

# create a sample dataframe
data = {'name': ['Bob', 'Alice', 'John', 'Doe'],
        'age': ['25', '22', '33', '18']}
df = pd.DataFrame(data)

# sort the dataframe in ascending order based on the 'age' column
df = df.sort_values('age', key=lambda x: pd.to_numeric(x, errors='coerce'))

print(df)

Output:

    name age
3    Doe  18
1  Alice  22
0    Bob  25
2   John  33

Note: The errors='coerce' parameter in the pd.to_numeric() function is used to convert any non-numeric value to NaN (Not a Number) instead of throwing an error. This allows non-numeric values to be handled properly during sorting.