PySpark provides, the **hex** function stands out when it comes to data transformations related to hexadecimal representation. This article sheds light on its utility, practical examples, and real-world use-cases. In PySpark, the **hex** function is used to convert numbers or binary strings into their corresponding hexadecimal representation.

Example of converting numbers to hexadecimal:

```
from pyspark.sql import SparkSession
from pyspark.sql.functions import hex
spark = SparkSession.builder \
.appName("Learning @ Freshers.in PySpark Hex Function") \
.getOrCreate()
data = [(10,), (255,), (1000,)]
df = spark.createDataFrame(data, ["numbers"])
df.withColumn("hex_value", hex(df["numbers"])).show()
```

**Output **

```
+-------+---------+
|numbers|hex_value|
+-------+---------+
| 10| A|
| 255| FF|
| 1000| 3E8|
+-------+---------+
```

**Use Case: MAC address transformation**

One practical scenario where `hex`

might be useful is when dealing with MAC addresses. Assume you’ve been given a dataset of MAC addresses without the usual colon (“:”) delimiters, and you’re tasked with extracting and converting each byte.

Let’s simulate this:

```
data = [("AABBCCDDEEFF",), ("112233445566",)]
df_mac = spark.createDataFrame(data, ["MAC_Address"])
# Extract and convert each byte pair
for i in range(6):
df_mac = df_mac.withColumn(f"byte_{i+1}", hex(df_mac["MAC_Address"].substr(i*2+1, 2)))
df_mac.show()
```

Output

```
+------------+------+------+------+------+------+------+
| MAC_Address|byte_1|byte_2|byte_3|byte_4|byte_5|byte_6|
+------------+------+------+------+------+------+------+
|AABBCCDDEEFF| 4141| 4242| 4343| 4444| 4545| 4646|
|112233445566| 3131| 3232| 3333| 3434| 3535| 3636|
+------------+------+------+------+------+------+------+
```

While this example is a simplification, in actual network datasets, the hex function can be essential in data transformation and cleaning tasks.

**When and where to use **`hex`

?

`hex`

?**Data Cleaning and Transformation:** Especially in IT and network datasets, where hexadecimal representation is common.

**Hashing and Encryption:** When dealing with hashes or encrypted data, the `hex`

function can aid in data transformation.

**Binary Data:** If your dataset contains raw binary data or BLOBs, converting it into a human-readable hex format can be useful for inspection or storage.

**Spark important urls to refer**