本文简要介绍 pyspark.pandas.DataFrame.drop_duplicates 的用法。用法:DataFrame.drop_duplicates(subset: Union[Any, Tuple[Any, …], List[Union[Any, Tuple[Any, …]]], None] = None, keep: str = 'first', inplace: bool = False)→ Optional[pyspark.pandas.frame.DataFrame]...
把.drop_duplicates("column_name")改为.drop_duplicates(subset=["column_name"])
select来选择你想要应用复制的列，并且返回的Dataframe只包含这些选定的列，而dropDuplicates(colNames)将在...
PySparkdistinct()transformation is used to drop/remove the duplicate rows (all columns) from DataFrame anddropDuplicates()is used to drop rows based on selected (one or multiple) columns.distinct()anddropDuplicates()returns a new DataFrame. In this article, you will learn how to use distinct()...
max_columns', 60) 混杂数据最重要的一个问题就是：怎么知道是否是混杂的数据。 下面准备使用 N ...
2 PySpark 22000 35days 3 Pandas 30000 50days Now applying thedrop_duplicates()function on the data frame as shown below, drops the duplicate rows. # Drop duplicates df1 = df.drop_duplicates() print(df1) Following is the output. # Output: ...
由于groupby不允许我在sparksql中执行上述查询,因此我删除了groupby,并在生成的Dataframe中使用了dropduplicates。以下是修改后的代码: from pyspark.sql import SparkSession spark = SparkSession \ .builder \ .appName("Python Spark SQL basic example") \ .config("spark.sql.crossJoin.enabled", "true") \...
PySpark The dropDuplicates function can be used for removing duplicate rows. df = df.dropDuplicates() It allows checking only some of the columns for determining the duplicate rows. df = df.dropDuplicates(["f1","f2"]) This question is also being asked as: ...
—drop_duplicates()，它可以帮助我们轻松地处理数据中的重复值。本文将详细介绍drop_duplicates()函数的...
本文简要介绍 pyspark.pandas.Index.drop_duplicates 的用法。用法:Index.drop_duplicates() → pyspark.pandas.indexes.base.Index返回删除重复值的索引。 返回: deduplicated: index 例子: 生成具有重复值的 pandas.Index。 >>> idx = ps.Index(['lama', 'cow', 'lama', 'beetle', 'lama', 'hippo'])...