duplicate_values = duplicate_rows.select(df.columns) 使用select()选择与原始数据框相同的列,即提取重复行的值。 替换重复行的值: 代码语言:txt 复制 df = df.dropDuplicates() 使用dropDuplicates()方法删除重复的行,即保留每个重复组中的第一行,并更新数据框。
To de-duplicate rows, use distinct, which returns only the unique rows.Python Копирај df_unique = df_customer.distinct() Handle null valuesTo handle null values, drop rows that contain null values using the na.drop method. This method lets you specify if you want to drop rows...
6.删除 去重dropDuplicates AI检测代码解析 # duplicate values df.count() # 33 # drop duplicate values df=df.dropDuplicates() # validate new count df.count() # 26 1. 2. 3. 4. 5. 6. 7. 8. 删除某列 AI检测代码解析 # drop column of dataframe df_new=df.drop('mobile') df_new.show...
PySpark – Distinct to drop duplicate rows PySpark orderBy() and sort() explained PySpark Groupby Explained with Example PySpark Join Types Explained with Examples PySpark Union and UnionAll Explained PySpark UDF (User Defined Function) PySpark flatMap() Transformation PySpark map Transformation PySpark...
数据集成转换 对于AWS Glue 4.0 及更高版本,使用key: --enable-glue-di-transforms, value: true创建或更新任务参数。 示例任务脚本: frompyspark.contextimportSparkContextfromawsgluedi.transformsimport* sc = SparkContext() input_df = spark.createDataFrame( [(5,), (0,), (-1,), (2,), (None,)...
('N/A')))# Drop duplicate rows in a dataset (distinct)df=df.dropDuplicates()# ordf=df.distinct()# Drop duplicate rows, but consider only specific columnsdf=df.dropDuplicates(['name','height'])# Replace empty strings with null (leave out subset keyword arg to replace in all columns)...
In the Aggregation drop down, select "AVG". display(train.select("hr", "cnt")) Visualization 02468101214161820220100200300400 hrcnt 24 aggregated rows. Train the machine learning pipeline Now that you have reviewed the data and prepared it as a DataFrame with numeric values, you're ready to...
Duplicate Values >>> df = df.dropDuplicates() Powered By Queries >>> from pyspark.sql import functions as F Powered By Select >>> df.select("firstName").show() #Show all entries in firstName column>>> df.select("firstName","lastName") \ .show()>>> df.select("firstName"...
ns))2、删除列.drop(''<字段名>'')删除库DROPDATABASEIFEXISTS]< 库名>;DELETEDATABASE<库名>ALL;在Parquet文件中:importsubprocess?subpro cess.check_call(''rm-r<存储路径>''),shell=True)在Hive表中:frompyspark.s qlimportHiveContexthive=HiveContext(spark.sparkContext)hive.s ...
>>> df.join(df2,'name','inner').drop('age','height').collect()[Row(name=u'Bob')] New in version 1.4. dropDuplicates(subset=None)[source] Return a new DataFrame with duplicate rows removed, optionally only considering certain columns. ...