本文简要介绍 pyspark.pandas.Series.drop_duplicates 的用法。用法:Series.drop_duplicates(keep: str = 'first', inplace: bool = False)→ Optional[pyspark.pandas.series.Series]返回删除重复值的系列。参数: keep:{‘first’, ‘last’, False },默认 ‘first’ 处理删除重复项的方法: - ‘first’ :...
把.drop_duplicates("column_name")改为.drop_duplicates(subset=["column_name"])
60 列 pd.set_option('display.line_width', 5000) pd.set_option('display.max_columns', 60) ...
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") \ ...
1. Differences Between PySpark distinct vs dropDuplicates The maindifference between distinct() vs dropDuplicates() functions in PySparkare the former is used to select distinct rows from all columns of the DataFrame and the latter is usedselect distinct on selected columns. ...
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...
—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...
For instance, drop_duplicates() removes the duplicate strings from the Series series, resulting in a new Series with only unique strings. import pandas as pd # Create a Series with duplicate strings series = pd.Series(['Spark', 'Pandas', 'Python', 'Pandas', 'PySpark']) # Drop ...
In this short how-to article, we will learn how to drop duplicate rows in Pandas and PySpark DataFrames. Pandas We can use the drop_duplicates function for this task. By default, it drops rows that are identical, which means the values in all the columns are the same. ...
最后,使用printSchema()方法打印了新的DataFrame的结构。 Pyspark中还提供了其他一些方法来删除列,例如select()方法可以选择需要保留的列,dropDuplicates()方法可以删除重复的行,filter()方法可以根据条件过滤行等。 对于Pyspark的更多信息和使用方法,可以参考腾讯云的相关产品和文档: 腾讯云Spark Pyspark API文档相关搜索:...