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。 这样,你就
Return a new DataFrame with duplicate rows removed, optionally only considering certain columns. 返回删除重复行的新 DataFrame,可选择仅考虑某些列。 drop_duplicates([subset]) drop_duplicates() is an alias for dropDuplicates(). dropna([how, thresh, subset]) Returns a new DataFrame omitting rows wit...
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 # 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 # drop column of dataframe df_new=df.drop('mobile') df_new.show(10) 1. 2. 3. 4. 7.保...
dropDuplicates() # or df = df.distinct() # Drop duplicate rows, but consider only specific columns df = df.dropDuplicates(['name', 'height']) # Replace empty strings with null (leave out subset keyword arg to replace in all columns) df = df.replace({"": None}, subset=["name"])...
AWS Glue 提供了以下可在 PySpark ETL 操作中使用的内置转换。您的数据在一个称为DynamicFrame的数据结构中从转换传递到转换,该数据结构是 Apache Spark SQLDataFrame的扩展。DynamicFrame包含您的数据,并引用其架构来处理您的数据。 此外,其中的大多数转换也将作为DynamicFrame类的方法存在。更多相关信息,请参阅Dynamic...
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"...
There is no duplicate records in the proposed test sets; therefore, the performance of the learners are not biased by the methods which have better detection rates on the frequent records. The number of selected records from each difficultylevel group is inversely proportional to the percentage of...
PySpark distinct() transformation is used to drop/remove the duplicate rows (all columns) from DataFrame and dropDuplicates() is used to drop rows based