把.drop_duplicates("column_name")改为.drop_duplicates(subset=["column_name"])
Pandas提供了一个功能强大的去重函数——drop_duplicates()，它可以帮助我们轻松地处理数据中的重复值。本...
(*columns_to_drop) #增加一列 from pyspark.sql.functions...,接下来将对这个带有缺失值的dataframe进行操作 # 1.删除有缺失值的行 clean_data=final_data.na.drop() clean_data.show() # 2.用均值替换缺失值...(authors, columns=["FirstName","LastName","Dob"]) df.drop_duplicates(subset=['...
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’ :...
1、去重dropDuplicates、distinct ff =d.select(['dnum']).dropDuplicates() ff.count() ff.show() fff =d.select(['dnum']).distinct() 1 2 3 4 2、withColumn、lit、col withColumn增加一列 lit 指定列 col 选择列 import pyspark.sql.functions as F temp_df = temp_df.withColumn("date", F....
pyspark:distinct和dropDuplicates区别 技术标签: # Spark文章目录 SPARK Distinct Function Spark dropDuplicates() Function distinct数据去重 使用distinct:返回当前DataFrame中不重复的Row记录。该方法和接下来的dropDuplicates()方法不传入指定字段时的结果相同。 dropDuplicates:根据指定字段去重 跟distinct方法不同的是,此...
print("Dropping duplicates strings:\n", result) # Output: # Dropping duplicates strings: # 0 Spark # 1 Pandas # 2 Python # 4 PySpark # dtype: object Frequently Asked Questions on Pandas Series drop duplicates() Function What is the purpose of the drop_duplicates() function in pandas Serie...
dropDisDF = df.dropDuplicates(["salary"]).select("salary") dropDisDF.show(truncate=False) print(dropDisDF.collect()) 5. Conclusion In this article, you have learned what is the difference between PySpark distinct and dropDuplicate functions, both these functions are from DataFrame class and ...
pandas框架，那么drop_duplicates将起作用。否则，如果你使用的是简单的pyspark框架，那么dropDuplicates将起...
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") \...