importorg.apache.spark.sql.SparkSessionvalspark=SparkSession.builder().appName("Change Column Order").getOrCreate()// 创建一个简单的 DataFramevaldata=Seq(("Alice",25,"Female"),("Bob",30,"Male"))valdf=spark.createDataFrame(data).toDF("Name","Age","Gender")// 变更列的顺序valnewDf=df...
AFTER: Column is added following row order Check if column exists importpandasaspddf=pd.DataFrame({'name':['alice','bob','charlie'],'age':[25,26,27]})candidate_names=['name','gender','age']fornameincandidate_names:ifnameindf.columns.values:print('"{}" is a column name'.format(name...
read_csv()函数:可以将frame文件直接读成frame。 movies=pd.read_csv(r'names\job1880.txt',names=column) read_csv函数有一个sep参数,设置分隔符,可以给这个参数传入正则表达式。 skiprows参数,参数是一个list,表示读取文件的时候,跳过list中的几行,第一行为0 read_excel()函数 可以直接读取excel文件为DataFram...
insert(loc, column, value[, allow_duplicates]) 在指定位置插入列到DataFrame中。 interpolate([method, axis, limit, inplace, ...]) 使用插值方法填充NaN值。 isetitem(loc, value) 在位置loc的列中设置给定值。 isin(values) 检查DataFrame中的每个元素是否包含在值中。 isna() 检测缺失值。 isnull() ...
方法描述DataFrame.pivot([index, columns, values])Reshape data (produce a “pivot” table) based on column values.DataFrame.reorder_levels(order[, axis])Rearrange index levels using input order.DataFrame.sort_values(by[, axis, ascending, …])Sort by the values along either axisDataFrame.sort_in...
如何调用?参数是Column对象wdchange($"weekdate") 入参/出参 是什么类型? udf{(sc:Int)=>{返回String}} udf{(sc:String)=>{返回Int}}//都没有问题 importorg.apache.spark.sql.functions._ val wdchange= udf{(num:Int)=>num match {case1 => "七"case2 => "一"case3 => "二"case4 => ...
pivot([index, columns, values]) #Reshape data (produce a “pivot” table) based on column values. DataFrame.reorder_levels(order[, axis]) #Rearrange index levels using input order. DataFrame.sort_values(by[, axis, ascending]) #Sort by the values along either axis DataFrame.sort_index([...
Clone(PrimitiveDataFrameColumn<Int32>, Boolean) (Inherited from PrimitiveDataFrameColumn<T>) Clone(PrimitiveDataFrameColumn<Int64>, Boolean) (Inherited from PrimitiveDataFrameColumn<T>) CloneImplementation(DataFrameColumn, Boolean, Int64) Clone column to produce a copy potentially changing the order of...
DataFrame.pivot([index, columns, values]) #Reshape data (produce a “pivot” table) based on column values. DataFrame.reorder_levels(order[, axis]) #Rearrange index levels using input order. DataFrame.sort_values(by[, axis, ascending]) #Sort by the values along either axis ...
用 stack 方法 参考链接：Reshaping and Pivot Tables In [26]: df = pd.DataFrame(np.random.randn...