使用mapPartitionsWithIndex 函数为 DataFrame 的每一行添加一个索引列: mapPartitionsWithIndex 会对每个分区及其索引进行迭代,并返回一个迭代器,其中包含处理后的行。我们可以利用这个函数来添加分区索引和行索引的组合作为新的列。 python def add_index_column(partition_index, iterator): row_index = 0 for row ...
Hi Brian, You shouldn't need to use exlode, that will create a new row for each value in the array. The reason max isn't working for your dataframe is because it is trying to find the max for that column for every row in you dataframe and not just the max in ...
Spark Dataframe :How to add a index Column : Aka Distributed Data Index 我在Apache-spark中有一个现有的数据集,我想根据索引从中选择一些行我计划添加一个包含从1开始的唯一值的索引列,并根据该列的值提取行。我找到了下面的方法来添加使用order by的索引: df.withCol 浏览41提问于2019-05-16得票数 2 ...
方法:使用函数的嵌套,将参数间接地传入。 from pyspark.sql import functions as f def generate_udf(constant_var): def test(col1, col2): if col1 == col2: return col1 else: return constant_var return f.udf(test, StringType()) df.withColumn('new_column',generate_udf('default_value')(f....
frompyspark.sqlimportSparkSessionfrompyspark.sql.functionsimportcol,lit,array# 创建SparkSessionspark=SparkSession.builder.appName("Add Array Column").getOrCreate()# 创建示例DataFramedata=[("Alice",34),("Bob",45),("Cathy",28)]df=spark.createDataFrame(data,["name","age"])# 添加一个固定数组...
增加、删除、修改列 pyspark # 增加列df.withColumn('add_column',df.group_num_c2+2)# 增加列 - 自定义函数frompyspark.sqlimportfunctionsasFdf.withColumn('add_column',F.UserDefinedFunction(lambdaobj:int(obj)+2)(df.group_num_c2))# 删除列df.drop('add_column')# 修改列名df.withColumnRenamed('gr...
用StringIndex加工qualification列 用StringIndex加工gender列 One hot encoding of a numeric column 使用Pipeline Part1 - StringIndexer 用法 详细内容请见: https://medium.com/@nutanbhogendrasharma/role-of-stringindexer-and-pipelines-in-pyspark-ml-feature-b79085bb8a6cmedium.com/@nutanbhogendrasharma/...
9.3 pyspark.sql.functions.add_months(start,months): New in version 1.5. 返回开始后几个月的日期 df=sqlContext.createDataFrame([('2015-04-08',)],['d']) df.select(add_months(df.d,1).alias('d')).collect() [Row(d=datetime.date(2015, 5, 8))] ...
for column in df.columns:df.describe(column).show() 1.4 分析每列是否包含缺失值 步骤4:分析每列是否包含缺失值,打印出有缺失值的样本数,占总数的比例。 df.filter(df['Type 2'].isNull()).count() # 386# 转换成pandas,打印出每一列的缺失值个数df.toPandas().isnull().sum()# 结果:Name 0Ty...
This post shows you how to fetch a random value from a PySpark array or from a set of columns. It'll also show you how to add a column to a DataFrame with a random value from a Python array and how to fetch n random values from a given column. ...