2.8. Read Python¶
pd.DataFrame()
2.8.1. Example¶
2.8.2. Assignments¶
"""
* Assignment: Pandas Read PythonDict
* Complexity: medium
* Lines of code: 8 lines
* Time: 8 min
English:
1. Convert `DATA` to format with one column per each attrbute for example:
a. `group1_year`, `group2_year`,
b. `group1_name`, `group2_name`
2. Note, that enumeration starts with one
3. Convert data to `result: pd.DataFrame`
4. Convert data in `group1_gid` and `group2_gid` to `int`
5. Run doctests - all must succeed
Polish:
1. Przekonweruj `DATA` do formatu z jedną kolumną dla każdego atrybutu, np:
a. `group1_year`, `group2_year`,
b. `group1_name`, `group2_name`
2. Zwróć uwagę, że enumeracja zaczyna się od jeden
3. Przekonwertuj dane do `result: pd.DataFrame`
4. Przekonwertuj dane w `group1_gid` i `group2_gid` do `int`
5. Uruchom doctesty - wszystkie muszą się powieść
Hint:
* dict.pop()
* enumerate(..., start=1)
* column_name = f'group{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 group1_gid group1_name group2_gid group2_name
0 Mark Watney 1 staff <NA> <NA>
1 Melissa Lewis 1 staff 2 admins
2 Rick Martinez <NA> <NA> <NA> <NA>
"""
import pandas as pd
DATA = [
{"firstname": "Mark", "lastname": "Watney", "groups": [
{"gid": 1, "name": "staff"}]},
{"firstname": "Melissa", "lastname": "Lewis", "groups": [
{"gid": 1, "name": "staff"},
{"gid": 2, "name": "admins"}]},
{"firstname": "Rick", "lastname": "Martinez", "groups": []},
]
# Define variable data with flatten ``DATA``
# Each group field prefixed with group and number
# type: list[dict]
data = ...
# Convert `data` to DataFrame
# type: pd.DataFrame
result = ...
"""
* Assignment: Pandas Read PythonObj
* Complexity: medium
* Lines of code: 7 lines
* Time: 13 min
English:
1. Read data from `DATA` as `result: pd.DataFrame`
2. Non-functional requirements:
a. Use `,` to separate mission fields
b. Use `;` to separate missions
2. Run doctests - all must succeed
Polish:
1. Wczytaj dane z DATA jako result: pd.DataFrame
2. Wymagania niefunkcjonalne:
a. Użyj `,` do oddzielania pól mission
b. Użyj `;` do oddzielenia missions
2. Uruchom doctesty - wszystkie muszą się powieść
Hints:
* `vars(obj)`
* dict.pop()
* Nested `for`
* `str.join(';', sequence)`
* `str.join(',', sequence)`
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 missions
0 Mark Watney 2035,Ares 3
1 Melissa Lewis 2030,Ares 1;2035,Ares 3
2 Rick Martinez
"""
import pandas as pd
class Astronaut:
def __init__(self, firstname, lastname, missions=None):
self.firstname = firstname
self.lastname = lastname
self.missions = list(missions) if missions else []
class Mission:
def __init__(self, year, name):
self.year = year
self.name = name
DATA = [
Astronaut('Mark', 'Watney', missions=[
Mission(2035, 'Ares 3')]),
Astronaut('Melissa', 'Lewis', missions=[
Mission(2030, 'Ares 1'),
Mission(2035, 'Ares 3')]),
Astronaut('Rick', 'Martinez', missions=[]),
]
# Convert DATA to list[dict], then flatten
# type: list[dict]
data = ...
# Convert `data` to DataFrame
# type: pd.DataFrame
result = ...