Передача нескольких переменных разных типов из фрейма данных в функцию

Question

У меня есть следующий фрейм данных:

import pandas as pd

data = {'selectionId': [8567238,7450487,12787737,9541421,10162696,7208966,8826166,7256678],

 'Price': [4.1,4.6,5.5,7.2,7.8,17.0,32.0,34.0],

 'Win_Percentage': [0.245870,0.212396,0.178922,0.145448,0.111974,0.078501,0.045027,0.011553],

  'Fit':[0.245870,0.212396,0.178922,0.145448,0.111974,0.078501,0.045027,0.011553],

   'size':[2.708701,2.373962,2.039223,1.704484,1.369744,1.035005,0.700266,0.365527]}

df = pd.DataFrame(data, columns=['selectionId', 'Price', 'Win_Percentage','Fit','size'])

У меня также есть следующая функция:

def test(marketId, selectionId):

    global place_order_Req

    place_order_Req = '{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"' + marketId + '","instructions":'\


'[{"selectionId":"' + str(
        selectionId) + '","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"1.9","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}'"""
print(place_order_Req)
"""

Переменная marketId всегда имеет значение marketId = "1.156196315"

Я хотел бы передать значение selectionId в df функции.

Я также хотел бы передать значения столбца размера в функцию, чтобы изменить "size":"1.9" часть функции.

Подводя итог, хотелось бы, чтобы из функции было возвращено следующее:

'{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"8567238","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"2.708701","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}\n    print(place_order_Req)\n    '

и для этого нужно выполнить для каждой строки кадра данных.

Для этого я попробовал следующее:

selectionId = df['selectionId']

size = df['size'].astype(str)

def test(marketId, selectionId, size):

    global place_order_Req, place_order_Req_list, place_order_Req_size_list

    place_order_Req_list = []

    place_order_Req_size_list = []

    for i in selectionId:
        place_order_Req = '{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"' + marketId + '","instructions":'\
                                                                                                                              '[{"selectionId":"' + str(
            i) + '","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"1","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}'
        """
    print(place_order_Req)
    """
        place_order_Req_list.append(place_order_Req)

    for j in place_order_Req_list:

        place_order_Req = place_order_Req[:208] + j + place_order_Req[:209]

        place_order_Req_size_list.append(place_order_Req)

    print(place_order_Req_size_list)

Это нормально меняет переменную selectionId, но когда я пытаюсь изменить "1.9", оно не работает. Он также возвращает себя дважды для каждого входа в список place_order_Req_size_list.

Я также думаю, что должен быть умнее, чем использование двух циклов.

Это список, который он возвращает:

['{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"8567238","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"1","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"', '{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7450487","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"1","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{', '{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"12787737","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"1","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{', '{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"9541421","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"1","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{', '{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"10162696","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"1","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{', '{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7208966","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"1","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{', '{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"8826166","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"1","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{', '{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"1","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"1.156196315","instructions":[{"selectionId":"7256678","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":{']

Любая помощь была бы отличной, ура. Sandy

Answer 1

Вы можете просто применить функцию к каждой строке вашего фрейма данных. Вы можете прочитать поля 'selectionId' и 'size' для каждой строки и передать их в переменную place_order_Req. Кроме того, я не уверен, что вам действительно нужно определить / использовать place_order_Req как глобальную переменную.

def test(x):    
    marketId = "1.156196315" #static value
    selectionId = x['selectionId']
    size = x['size']

#     global place_order_Req
    place_order_Req = '{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"' + marketId + '","instructions":' '[{"selectionId":"' + str(selectionId) + '","handicap":"0","side":"BACK","orderType":"LIMIT", "limitOrder":{"size": "'+ str(size) + '","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}'
    print(place_order_Req)

df.apply(test, axis=1)

Answer 2

Вы можете использовать apply:

def query(marketId, selectionId, size):

    global place_order_Req

    place_order_Req = '{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"' + marketId + '","instructions":'\
                      '[{"selectionId":"' + str(selectionId) + '","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"' \
                      + str(size) + '","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}'

    return place_order_Req

marketId = "1.156196315"
queries = df.apply(lambda x: query(marketId, x.selectionId, x.size), axis=1)

queries_list = queries.values.tolist() # list of your queries strings

Answer 3

Я сейчас рассмотрел код, и он работает со следующим, но я все еще думаю, что должен быть лучший метод, чем использование двух циклов:

size = df['size'].astype(str)
size = '"' + size + '"'

def test(marketId, selectionId, size):

    global place_order_Req, place_order_Req_list, place_order_Req_size_list

    place_order_Req_list = []

    place_order_Req_size_list = []

    for i in selectionId:
        place_order_Req = '{"jsonrpc": "2.0", "method": "SportsAPING/v1.0/placeOrders", "params": {"marketId":"' + marketId + '","instructions":'\
                                                                                                                              '[{"selectionId":"' + str(
            i) + '","handicap":"0","side":"BACK","orderType":"LIMIT","limitOrder":{"size":"1","price":"1.1","persistenceType":"LAPSE"}}],"customerRef":"test12121212121"}, "id": 1}'
        """
    print(place_order_Req)
    """
        place_order_Req_list.append(place_order_Req)

    for j in size:

        place_order_Req = place_order_Req[:208] + j + place_order_Req[:209]

        place_order_Req_size_list.append(place_order_Req)

    print(place_order_Req_size_list)