Question

我想通过JSON接收的值来过滤数据框，如下所示：

region = request_json['region_value']
ma = request_json['ma_value']
market = request_json['market_value']
subsegment = request_json['subsegment_value']

filtered =df[
    (df['Region'] == region) &
    (df['MA/Segment'] == ma) &
    (df['Market'] == market) &
    (df['Subsegment'] == subsegment)
]

但是，如果region，ma，market或subsegment等于'All'，我不想在过滤中包括它。

例如，如果region = 'All'，则代码应如下所示：

filtered =df[
        (df['MA/Segment'] == ma) &
        (df['Market'] == market) &
        (df['Subsegment'] == subsegment)
    ]

我想避免使用多个if，而是寻求更优雅的解决方案。我欢迎任何想法。

Answer 1

您可以使用np.logical_and.reduce;即使您的列名包含空格，特殊字符等，此方法也将起作用：

conditions = {
    'Region': region, 'MA/Segment': ma, 'Market': market, 'Subsegment': subsegment}

mask = pd.np.logical_and.reduce([
    df[k] == v for k, v in conditions.items() if v != 'All'])
df[mask]

另一个选项是query，但这将在您的列名称符合有效的python标识符名称的情况下起作用。

query = ' and '.join([
    f'{k}=={repr(v)}' for k, v in conditions.items() if v != 'All'])    
df.query(query)

Answer 2

使用try: import thatpackage except Exception as e: print("importing thatpackage failed", e)

sum

仅当值不是特定值时才按值过滤数据帧

2 个答案: