What is the best way to approach this problem?

Check out this blog code to learn how to fix errors.

JS Problems geeksforgeeks Exercises and Solutions for Beginners

How to Change a Column Type of a DataFrame in PySpark [All Method]️

Richard ParkerFebruary 8, 2022

1 minute read

How to Change a Column Type of a DataFrame in PySpark [All Method]️ — How to Change a Column Type of a DataFrame in PySpark All Method

The blog will help about How to Change a Column Type of a DataFrame in PySpark & learn how to solve different problems that come from coding errors. If you get stuck or have questions at any point,simply comment below.
Question: What is the best solution for this problem? Answer: This blog code can help you solve errors How to Change a Column Type of a DataFrame in PySpark. Question: “What should you do if you run into code errors?” Answer:”You can find a solution by following this blog.

How can we change the column type of a DataFrame in PySpark?

Suppose we have a DataFrame df with column num of type string.

Let’s say we want to cast this column into type double.

Luckily, Column provides a cast() method to convert columns into a specified data type.

Cast using `cast()` and the singleton `DataType`

We can use the PySpark DataTypes to cast a column type.

from pyspark.sql.types import DoubleType
df = df.withColumn("num", df["num"].cast(DoubleType()))
# OR
df = df.withColumn("num", df.num.cast(DoubleType()))

We can also use the col() function to perform the cast.

from pyspark.sql.functions import col
from pyspark.sql.types import DoubleType
df = df.withColumn("num", col("num").cast(DoubleType()))

Cast using `cast()` and simple strings

We can also use simple strings.

How to console.log with colors in JavaScript 📌[All Method]️

from pyspark.sql.types import DoubleType
df = df.withColumn("num", df["num"].cast("double"))
# OR
df = df.withColumn("num", df.num.cast("double"))

Get simple string from `DataType`

Here is a list of DataTypes to simple strings.

BinaryType: binary
BooleanType: boolean
ByteType: tinyint
DateType: date
DecimalType: decimal(10,0)
DoubleType: double
FloatType: float
IntegerType: int
LongType: bigint
ShortType: smallint
StringType: string
TimestampType: timestamp

Simple strings for any DataType can be obtained using getattr() and simpleString().

We can get the simple string for any DataType like so:

from pyspark.sql import types
simpleString = getattr(types, 'BinaryType')().simpleString()

from pyspark.sql.types import BinaryType
simpleString = BinaryType().simpleString()

We can also write out simple strings for arrays and maps: array<int> and map<string,int>.

Read more about cast() here.

Revise the code and make it more robust with proper test case and check an error there before implementing into a production environment.
Now you can solve your code error in less than a minute.