In case youneed a helper method, use: object DFHelper{ def castColumnTo( df: DataFrame, cn: String, type: DataType ) : DataFrame = { df.withColumn( cn, df(cn).cast(type) ) } } which is used like: import DFHelper._ val df2 = castColumnTo( df, "year", IntegerType ) If you...
Data Wrangler, a notebook-based tool for exploratory data analysis, now supports both Spark DataFrames and pandas DataFrames, generating PySpark code in addition to Python code. For a general overview of Data Wrangler, which covers how to explore and transform pandas DataFrames, see the the ...
Data Wrangler, a notebook-based tool for exploratory data analysis, now supports both Spark DataFrames and pandas DataFrames, generating PySpark code in addition to Python code. For a general overview of Data Wrangler, which covers how to explore and transform pandas DataFrames, see the the ...
Data Wrangler, a notebook-based tool for exploratory data analysis, now supports both Spark DataFrames and pandas DataFrames, generating PySpark code in addition to Python code. For a general overview of Data Wrangler, which covers how to explore and transform pandas DataFrames, see the the ...
Data Wrangler, a notebook-based tool for exploratory data analysis, now supports both Spark DataFrames and pandas DataFrames, generating PySpark code in addition to Python code. For a general overview of Data Wrangler, which covers how to explore and transform pandas DataFrames, see the the ...
Data Wrangler, a notebook-based tool for exploratory data analysis, now supports both Spark DataFrames and pandas DataFrames, generating PySpark code in addition to Python code. For a general overview of Data Wrangler, which covers how to explore and transform pandas DataFrames, see the the ...