הערה
הגישה לדף זה מחייבת הרשאה. באפשרותך לנסות להיכנס או לשנות מדריכי כתובות.
הגישה לדף זה מחייבת הרשאה. באפשרותך לנסות לשנות מדריכי כתובות.
Check if the column value is between lower and upper bounds (inclusive).
Syntax
between(lowerBound, upperBound)
Parameters
| Parameter | Type | Description |
|---|---|---|
lowerBound |
value or Column | Lower bound value |
upperBound |
value or Column | Upper bound value |
Returns
Column (boolean)
Examples
Using between with integer values:
df = spark.createDataFrame([(2, "Alice"), (5, "Bob")], ["age", "name"])
df.select(df.name, df.age.between(2, 4)).show()
# +-----+---------------------------+
# | name|((age >= 2) AND (age <= 4))|
# +-----+---------------------------+
# |Alice| true|
# | Bob| false|
# +-----+---------------------------+
Using between with string values:
df = spark.createDataFrame([("Alice", "A"), ("Bob", "B")], ["name", "initial"])
df.select(df.name, df.initial.between("A", "B")).show()
# +-----+-----------------------------------+
# | name|((initial >= A) AND (initial <= B))|
# +-----+-----------------------------------+
# |Alice| true|
# | Bob| true|
# +-----+-----------------------------------+
Using between with float values:
df = spark.createDataFrame(
[(2.5, "Alice"), (5.5, "Bob")], ["height", "name"])
df.select(df.name, df.height.between(2.0, 5.0)).show()
# +-----+-------------------------------------+
# | name|((height >= 2.0) AND (height <= 5.0))|
# +-----+-------------------------------------+
# |Alice| true|
# | Bob| false|
# +-----+-------------------------------------+
Using between with date values:
import pyspark.sql.functions as sf
df = spark.createDataFrame(
[("Alice", "2023-01-01"), ("Bob", "2023-02-01")], ["name", "date"])
df = df.withColumn("date", sf.to_date(df.date))
df.select(df.name, df.date.between("2023-01-01", "2023-01-15")).show()
# +-----+-----------------------------------------------+
# | name|((date >= 2023-01-01) AND (date <= 2023-01-15))|
# +-----+-----------------------------------------------+
# |Alice| true|
# | Bob| false|
# +-----+-----------------------------------------------+
Using between with timestamp values:
import pyspark.sql.functions as sf
df = spark.createDataFrame(
[("Alice", "2023-01-01 10:00:00"), ("Bob", "2023-02-01 10:00:00")],
schema=["name", "timestamp"])
df = df.withColumn("timestamp", sf.to_timestamp(df.timestamp))
df.select(df.name, df.timestamp.between("2023-01-01", "2023-02-01")).show()
# +-----+---------------------------------------------------------+
# | name|((timestamp >= 2023-01-01) AND (timestamp <= 2023-02-01))|
# +-----+---------------------------------------------------------+
# |Alice| true|
# | Bob| false|
# +-----+---------------------------------------------------------+