Python 如何获取数据帧中列的架构(不是所有架构)?
我有一个数据帧后,平坦的操作 我想要返回到原始数据帧 例如: Df: 我有一个数据帧(展平),如: 平面图(新):Python 如何获取数据帧中列的架构(不是所有架构)?,python,dataframe,apache-spark,pyspark,Python,Dataframe,Apache Spark,Pyspark,我有一个数据帧后,平坦的操作 我想要返回到原始数据帧 例如: Df: 我有一个数据帧(展平),如: 平面图(新): delivery_from_time: string (nullable = true) delivery_to_time: string (nullable = true) delivery_delivery_start_date_time: string (nullable = true) delivery_delivery_end_date_time: string (
delivery_from_time: string (nullable = true)
delivery_to_time: string (nullable = true)
delivery_delivery_start_date_time: string (nullable = true)
delivery_delivery_end_date_time: string (nullable = true)
delivery_duration: string (nullable = true)
delivery_delivery_capacity_quantity: string (nullable = true)
delivery_quantity_unit: string (nullable = true)
flat_df_new是扁平化数据帧(分解所有结构类型)及其操作
parentList是以df原始格式分解的数组结构的列表
父项列表中的父项的:
df_temp=df.select(父)。模式是否只需首先选择该列?比如df.select('delivery').printSchema()
yes ok,但现在我想在df1中添加一列,比如:df是原始数据帧:flat_df_new是展平数据帧(esplode all struct Type)和对它的操作:parentList是在df-original中分解的数组结构列表。对于parentList中的父项:df_temp=df.select(parent).schema
delivery_from_time: string (nullable = true)
delivery_to_time: string (nullable = true)
delivery_delivery_start_date_time: string (nullable = true)
delivery_delivery_end_date_time: string (nullable = true)
delivery_duration: string (nullable = true)
delivery_delivery_capacity_quantity: string (nullable = true)
delivery_quantity_unit: string (nullable = true)