如何过滤pyspark dataframe中的日期

Question

I have a pyspark dataframe:

Year    Month
2021    06/01/2021
2021    06/01/2021
2021    07/01/2021
2021    07/01/2021
2021    0/01/2021
2021    0/01/2021

I need a dataframe for specific months along with '0/01/2021'. Tried with below code:

df=df.filter((col('Month')=='07/01/2021') & (col('Month')=='0/01/2021'))
display(df)

My required dataframe is:

Year    Month
2021    07/01/2021
2021    07/01/2021
2021    0/01/2021
2021    0/01/2021

But I'm getting: Query returned no results as result. The 'Month' column is in string format. How to filter for these dates?

Answer 1

That's normal. You are asking for each line that the value equal both 07/01/2021 AND ( & ) 0/01/2021.
What you are the lines where month = 07/01/2021 OR ( | ) 0/01/2021:

from pyspark.sql.functions import col

a = [
    (2021, "06/01/2021"),
    (2021, "06/01/2021"),
    (2021, "07/01/2021"),
    (2021, "07/01/2021"),
    (2021, "0/01/2021"),
    (2021, "0/01/2021"),
]

b = "Year", "Month"

df = spark.createDataFrame(a, b)
df = df.filter((col("Month") == "07/01/2021") | (col("Month") == "0/01/2021"))
# 
df.show()
+----+----------+                                                               
|Year|     Month|
+----+----------+
|2021|07/01/2021|
|2021|07/01/2021|
|2021| 0/01/2021|
|2021| 0/01/2021|
+----+----------+

you can also write is like this:

df.filter(col("Month").isin("07/01/2021", "0/01/2021")).show()