Question

我正在寻求有关如何改进此程序和更有效地使用熊猫的建议。

我有一个来自市场的订单数据集。每个订单都是针对代表商品的type_id进行的，可以是买入或卖出订单，并具有价格和数量。

我要处理市场数据，并创建一个包含每个type_id的DataFrame，以及为该商品买卖n％的交易量的成本。

这是我的工作代码：

import pandas as pd

type_ids = {
    0: 'Item A',
    1: 'Item B',
}

market_order_list = [
    {'type_id': 0, 'is_buy_order': False, 'price': 80, 'volume': 22},
    {'type_id': 0, 'is_buy_order': False, 'price': 70, 'volume': 12},
    {'type_id': 0, 'is_buy_order': False, 'price': 60, 'volume': 9},

    {'type_id': 0, 'is_buy_order': True, 'price': 50, 'volume': 3},
    {'type_id': 0, 'is_buy_order': True, 'price': 40, 'volume': 9},
    {'type_id': 0, 'is_buy_order': True, 'price': 30, 'volume': 33},

    {'type_id': 1, 'is_buy_order': False, 'price': 30, 'volume': 28},
    {'type_id': 1, 'is_buy_order': False, 'price': 25, 'volume': 11},
    {'type_id': 1, 'is_buy_order': False, 'price': 20, 'volume': 7},

    {'type_id': 1, 'is_buy_order': True, 'price': 15, 'volume': 8},
    {'type_id': 1, 'is_buy_order': True, 'price': 10, 'volume': 12},
    {'type_id': 1, 'is_buy_order': True, 'price': 5, 'volume': 24}
]

def inner_func(df, tracking):
    if tracking['volume_processed'] == tracking['total_volume_to_process']:
        # We already filled our total volume, no more processing needed
        return

    # We need to process this much more volume
    needed_volume = tracking['total_volume_to_process'] - tracking['volume_processed']

    if df['volume'] >= needed_volume:
        # This order can fully fill us
        tracking['volume_processed'] += needed_volume
        tracking['total_price_paid'] += needed_volume * df['price']
    else:
        # This order can only partially fill us
        tracking['volume_processed'] += df['volume']
        tracking['total_price_paid'] += df['volume'] * df['price']

def outer_func(df_orig, result_list, percent):
    # Determine if this is a list of buy or sell orders and get the type
    is_buy = df_orig['is_buy_order'][0]
    type_id = df_orig['type_id'][0]

    # Sort price in correct direction for buy/sell, and calculate how much volume is needed
    df = df_orig.sort_values('price', ascending=not is_buy, inplace=False).reset_index(drop=True)
    total_volume_to_process = int(df['volume'].sum() * percent)

    # Make tracking dictionary which will capture results of this set of orders
    tracking = {
        'type_id': type_id,
        'is_buy': is_buy,
        'volume_processed': 0,
        'total_volume_to_process': total_volume_to_process,
        'total_price_paid': 0,
    }

    # Each inner_func call will be just the buy side, or just the sell side, for a single type_id
    df.apply(func=inner_func, axis=1, args=(tracking,))

    # Append the results to our list
    result_list.append(tracking)

result_list = []

# Load the dataframe
df = pd.DataFrame(market_order_list)
g = df.groupby(['type_id', 'is_buy_order']).apply(outer_func, result_list=result_list, percent=0.33)

# Load the result_list into a dataframe and display
result_frame = pd.DataFrame(result_list)
print('=== Result === ')
print(result_frame)
print('\nWhat is the cost of buying 33% of the volume for type_id = 0?')
total_price_paid = result_frame[(result_frame.type_id == 0) & (result_frame.is_buy == True)]['total_price_paid'].item()
print(total_price_paid)

这是输出：

=== Result === 
   type_id  is_buy  volume_processed  total_volume_to_process  total_price_paid
0        0   False                14                       14               890
1        0    True                14                       14               570
2        1   False                15                       15               340
3        1    True                14                       14               180


What is the cost of buying 33% of the volume for type_id = 0?
570

请给我一些有关我的工作方式和改进方法的建议。进行此操作的正确方法是什么？谢谢。

在DataFrame中处理数据的最佳方法

0 个答案: