In this PySpark article, you have learned how to cast or change one DataFrame column Data Type to another type using withColumn(), selectExpr(), SQL. This example is also available at GitHub for reference. withColumn("jobStartDate",col("jobStartDate").cast(DateType())) withColumn("isGraduated",col("isGraduated").cast(BooleanType())) \ Spark = ('').getOrCreate()įrom import StringType,BooleanType,DateTypeĭf2 = df.withColumn("age",col("age").cast(StringType())) \ Complete Example of Casting PySpark Columnīelow is complete working example of how to convert the data types of DataFrame column. is SAS format ('informat', to be exact) that tries to read in as many reasonable numeric formats as possible, it will work in. You need to replace yourstringvariable and yournewnumericvariable appropriately. On SQL just wrap the column with the desired type you want.ĭf3.createOrReplaceTempView("CastExample")ĭf4 = spark.sql("SELECT STRING(age),BOOLEAN(isGraduated),DATE(jobStartDate) from CastExample")ĥ. Probably the best way would be to use: input (yourstringvariable, best.) as yournewnumericvariable. In order to use on SQL, first, we need to create a table using createOrReplaceTempView(). We can also use PySpark SQL expression to change/cast the spark DataFrame column type. "cast(jobStartDate as string) jobStartDate") "cast(isGraduated as string) isGraduated", This example uses the CAST expression to convert a decimal to an. 1) Converting a decimal to an integer example example. STR (floatexpression ,length ,decimal) Example: SELECT STR (123.45, 6, 1) as Num2 Output: 123.5. Let’s take some examples of using the CAST expression. Using Str () STR () is another function in SQL Server that accepts number values and returns them as a varchar expression and character data is right-justified, with a specified length and decimal precision.
#SQL CONVERT STRING TO INT CODE#
SelectExpr() is a function in DataFrame which we can use to convert spark DataFrame column “age” from String to integer, “isGraduated” from boolean to string and “jobStartDate” from date to String.ĭf3 = df2.selectExpr("cast(age as int) age", Code language: SQL (Structured Query Language) (sql) In this syntax, you specify the value and the data type to which you want to convert the value. |- isGraduated: boolean (nullable = true) SELECT CAST (CAST (MyVarcharCol AS NUMERIC (19,4)) AS INT) When copying data from TableA to TableB, the conversion is implicit, so you dont need the second convert (if you are happy rounding down to nearest INT): INSERT INTO TableB (MyIntCol) SELECT CAST. Use withColumn() to convert the data type of a DataFrame column, This function takes column name you wanted to convert as a first argument and for the second argument apply the casting method cast() with DataType on the column. To get around this just do two converts as follows: STRING -> NUMERIC -> INT. |firstname|age|jobStartDate|isGraduated|gender|salary| |- jobStartDate: string (nullable = true)
Use the optional M and D parameters to specify the maximum number of digits (M) and the number of digits following the decimal point (D). ("Robert",37,"06-01-1992","false","M",5000.50)Ĭolumns = ĭf = spark.createDataFrame(data = simpleData, schema = columns) Can be one of the following: Converts value to DATE.
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