Data Dictionaries in Python

[DeaD_EyE]

You can make a filter-function.
Instead of jumping directly into pandas, you should know also the Python stuff.

def filter_by(data, **kwargs):
    for row in data:
         for key, value in kwargs.items():
             if row.get(key) != value:
                 break
         else:
             yield row


# if the results are saved in the list result
list(filter_by(result, Pos='4'))

In this example I do not type conversion. It's just a string comparison of equality.
The else-block of the for-loop is only then executed, if the for-loop has finished the iteration.
Breaking early out of the loop, will not execute the else-block of the for-loop.
This means only if all keys are existing and return the wanted values, it will yield a hit.
The use of dict.get() is mandatory, if you don't check if the wanted key exist.
Otherwise you'll get a KeyError.
The get method on a dict, return by default None, if the key does not exist.
You can define the default values as second argument in the get method.

The function itself return a generator, if called. The generator does nothing until
it's consumed by a for-loop or types like tuple, list, set, etc...
If you see in a function a yield statement, then it's a generator.

Generators can do funny stuff, like generating infinite sequences.