![]() ![]() It all depends on which string values you want to consider as True and which string values you want to consider as False. convertbooleanbool, defaults True Whether object dtypes should be converted to BooleanDtypes (). convertintegerbool, default True Whether, if possible, conversion can be done to integer extension types. Note that the above example is a very specific use case. convertstringbool, default True Whether object dtypes should be converted to StringDtype (). We get True as the output for the string “true”. # string to boolean functionĮlif s in ("False", "FALSE", "false", "0"): We get True for the string having the value “True” and False for the string having the value “False”.Īlternatively, if you want a more exhaustive match for a string containing truth values like “True”, “1”, “TRUE”, “true”, etc. If you want to convert a string containing truth values such as “True” or “False” to boolean, you can use the equality operator to compare them with “True” and “False” and return a boolean value. Convert string truth values to boolean in Python We get True as the output for both the strings. So even if you pass truth values in string form, for example, “True” or “False”, you’ll get the same result. Note that the result from the bool() function depends on whether the passed string is empty or not. Let’s look at another example, this time with an empty string. We get True as the output because the string s above is non-empty. Let’s look at some examples of using the above function. It returns True for non-empty string and False for empty strings. The following is the syntax – # string to boolean Pass the string as an argument to the function. You can use the built-in bool() function to convert a string to a boolean in Python. How to convert string to a boolean in Python? ![]() ![]() In this PySpark article, you have learned how to cast or change one DataFrame column Data Type to another type using withColumn(), selectExpr(), SQL.In this tutorial, we will look at how to convert a string to a boolean in Python with the help of some examples. 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. 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. 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", 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", |- isGraduated: boolean (nullable = true) 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. ![]() |firstname|age|jobStartDate|isGraduated|gender|salary| |- jobStartDate: string (nullable = true) Let’s run with an example, first, create simple DataFrame with different data types. Spark.sql("SELECT INT(age),BOOLEAN(isGraduated),DATE(jobStartDate) from CastExample") From import IntegerType,BooleanType,DateTypeĭf.withColumn("age",df.age.cast(IntegerType()))ĭf.withColumn("age",df.age.cast('integer'))ĭf.select(col("age").cast('int').alias("age")) ![]()
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