将 DataFrame 的 DataFrame 转换为单个 DataFrame 仅选择某些列 Python

Question

我有下一个Json文件：

exchangeInfo = {
    "timezone": "UTC",
    "serverTime": 1565246363776,
    "rateLimits": [],
    "exchangeFilters": [],
    "symbols": [
        {
            "symbol": "ETHBTC",
            "status": "TRADING",
            "baseAsset": "ETH",
            "baseAssetPrecision": 8,
            "quoteAsset": "BTC",
            "quotePrecision": 8,
            "quoteAssetPrecision": 8,
            "baseCommissionPrecision": 8,
            "quoteCommissionPrecision": 8,
            "filters": [
                {
                    "filterType": "PRICE_FILTER",
                    "minPrice": "0.00000100",
                    "maxPrice": "100000.00000000",
                    "tickSize": "0.00000100",
                },
                {
                    "filterType": "PERCENT_PRICE",
                    "multiplierUp": "1.3000",
                    "multiplierDown": "0.7000",
                    "avgPriceMins": 5,
                },
                {
                    "filterType": "LOT_SIZE",
                    "minQty": "0.00100000",
                    "maxQty": "100000.00000000",
                    "stepSize": "0.00100000",
                },
            ],
        },
    ],
}

然后应用下一个代码，我将“过滤器”列转换为列。

df = pd.json_normalize(exchangeInfo["symbols"])
df = pd.concat(
    [
        df,
        df.pop("filters")
        .apply(lambda x: dict(i for d in x for i in d.items()))
        .apply(pd.Series),
    ],
    axis=1,
).drop(columns="filterType")
print(df)

打印：

symbol   status baseAsset  baseAssetPrecision quoteAsset  quotePrecision  quoteAssetPrecision  baseCommissionPrecision  quoteCommissionPrecision    minPrice         maxPrice    tickSize multiplierUp multiplierDown  avgPriceMins      minQty           maxQty    stepSize
0  ETHBTC  TRADING       ETH                   8        BTC               8                    8                        8                         8  0.00000100  100000.00000000  0.00000100       1.3000         0.7000             5  0.00100000  100000.00000000  0.00100000

但是，我只想 select 这些过滤器中的 2 个，按 filterType 名称，我想要“PRICE_FILTER”和“LOT_SIZE”

Answer 1

您需要列出所需的过滤器，然后select列表中的任何过滤器：

filters = ['PRICE_FILTER', 'LOT_SIZE']
df = df[df['filters'].str.isin('|'.join(filters))]

Answer 2

要仅从“PRICE_FILTER”和“LOT_SIZE”过滤器中获取列，请尝试：

df = pd.json_normalize(exchangeInfo["symbols"])
df = pd.concat(
    [
        df,
        df.pop("filters")
        .apply(
            lambda x: dict(
                i
                for d in x
                for i in d.items()
                if d["filterType"] in {"PRICE_FILTER", "LOT_SIZE"}
            )
        )
        .apply(pd.Series),
    ],
    axis=1,
).drop(columns="filterType")
print(df)

打印：

   symbol   status baseAsset  baseAssetPrecision quoteAsset  quotePrecision  quoteAssetPrecision  baseCommissionPrecision  quoteCommissionPrecision    minPrice         maxPrice    tickSize      minQty           maxQty    stepSize
0  ETHBTC  TRADING       ETH                   8        BTC               8                    8                        8                         8  0.00000100  100000.00000000  0.00000100  0.00100000  100000.00000000  0.00100000

将 DataFrame 的 DataFrame 转换为单个 DataFrame 仅选择某些列 Python

Transform DataFrame of Dataframe into Single DataFrame Selecting only Some Columns Python

python

dataframe

pandas

binance