"""
* Assignment: Pandas Read PythonDict
* Complexity: medium
* Lines of code: 8 lines
* Time: 13 min

English:
    1. Convert `DATA` to format with one column per each attrbute for example:
       a. `mission1_year`, `mission2_year`,
       b. `mission1_name`, `mission2_name`
    2. Note, that enumeration starts with one
    3. Convert data to `result: pd.DataFrame`
    4. Run doctests - all must succeed

Polish:
    1. Przekonweruj `DATA` do formatu z jedną kolumną dla każdego atrybutu, np:
       a. `mission1_year`, `mission2_year`,
       b. `mission1_name`, `mission2_name`
    2. Zwróć uwagę, że enumeracja zaczyna się od jeden
    3. Przekonwertuj dane do `result: pd.DataFrame`
    4. Uruchom doctesty - wszystkie muszą się powieść

Hint:
    * dict.pop()
    * enumerate(..., start=1)
    * column_name = f'mission{i}_{field}'

Tests:
    >>> import sys; sys.tracebacklimit = 0

    >>> assert result is not Ellipsis, \
    'Assign result to variable: `result`'
    >>> assert type(result) is pd.DataFrame, \
    'Variable `result` has invalid type, should be `pd.DataFrame`'

    >>> result  # doctest: +NORMALIZE_WHITESPACE
      firstname  lastname mission1_year mission1_name mission2_year mission2_name
    0      Mark    Watney          2035         Ares3           NaN           NaN
    1   Melissa     Lewis          2030         Ares1          2035         Ares3
    2      Rick  Martinez           NaN           NaN           NaN           NaN
"""
import pandas as pd


DATA = [
    {"firstname": "Mark", "lastname": "Watney", "missions": [
        {"year": "2035", "name": "Ares3"}]},

    {"firstname": "Melissa", "lastname": "Lewis", "missions": [
         {"year": "2030", "name": "Ares1"},
         {"year": "2035", "name": "Ares3"}]},

    {"firstname": "Rick", "lastname": "Martinez", "missions": []}
]


# Define variable data with flatten ``DATA``
# Each mission field prefixed with mission and number
# type: list[dict]
data = ...

# Convert `data` to DataFrame
# type: pd.DataFrame
result = ...


# Solution
data = []
for astronaut in DATA:
    for i, mission in enumerate(astronaut.pop('missions'), start=1):
        for field,value in mission.items():
            column_name = f'mission{i}_{field}'
            astronaut[column_name] = value
    data.append(astronaut)

result = pd.DataFrame(data)