要找到两个pyarrow数据集模式的不同之处,可以通过以下步骤进行比较:
import pyarrow as pa
import pandas as pd
dataset1 = pa.dataset.dataset("path_to_dataset1")
dataset2 = pa.dataset.dataset("path_to_dataset2")
schema1 = dataset1.schema
schema2 = dataset2.schema
num_fields1 = len(schema1)
num_fields2 = len(schema2)
field_names1 = [field.name for field in schema1]
field_names2 = [field.name for field in schema2]
field_types1 = [field.type for field in schema1]
field_types2 = [field.type for field in schema2]
fields_match = schema1.equals(schema2)
fields_order_match = field_names1 == field_names2
types_match = field_types1 == field_types2
print("字段数量不同:" + str(num_fields1 != num_fields2))
print("字段名称不同:" + str(field_names1 != field_names2))
print("字段类型不同:" + str(field_types1 != field_types2))
print("字段完全一致:" + str(fields_match))
print("字段顺序一致:" + str(fields_order_match))
print("字段类型一致:" + str(types_match))
这样,你就可以找到两个pyarrow数据集模式的不同之处。请注意,以上代码仅适用于pyarrow版本1.0.0及以上。对于更早的版本,可能需要进行适当的调整。
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