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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def addTable(D):
 """ Add any table type to the given dataset. Use prompts to determine index locations and table type. :param dict D: Metadata (dataset) :param dict dat: Metadata (table) :return dict D: Metadata (dataset) """


    _swap = {
        "1": "measurement",
        "2": "summary",
        "3": "ensemble",
        "4": "distribution"
    }


    print("What type of table would you like to add?\n"
          "1: measurement\n"
          "2: summary\n"
          "3: ensemble (under development)\n"
          "4: distribution (under development)\n"
          "\n Note: if you want to add a whole model, use the addModel() function")
    _ans = input(">")

    if _ans in ["3", "4"]:
        print("I don't know how to do that yet.")
    # if this is a summary or measurement, split the csv into each column
    elif _ans in ["1", "2"]:
        # read in a csv file. have the user point to it
        print("Locate the CSV file with the values for this table: ")
        _path, _files = browse_dialog_file()

        _path = _confirm_file_path(_files)
        _values = read_csv_from_file(_path)
        _table = _build_table(_values)
        _placement = _prompt_placement(D, _swap[_ans])
        D = _put_table(D, _placement, _table)

    else:
        print("That's not a valid option")

    return D