把.drop_duplicates("column_name")改为.drop_duplicates(subset=["column_name"])
5000) pd.set_option('display.max_columns', 60) 混杂数据最重要的一个问题就是：怎么知道是否是...
—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...
By default, the first occurrence of duplicate rows is kept in the DataFrame and the other ones are dropped. We also have the option to keep the last occurrence. # keep the last occurrencedf = df.drop_duplicates(subset=["f1","f2"],keep="last") PySpark The dropDuplicates function can be...
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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’ :...
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 ...
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 ...
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...
I think @afnanurrahim Dropping duplicates in large PySpark datasets can be tricky, especially when filtering on subsets. My initial window function approach turned out sluggish for df2.count() due to unnecessary shuffling and sorting. Some options maybe to be considered: dropDuplicates: Simplest so...