Convert pyspark string to date format

Developers
1

I have a date pyspark dataframe with a string column in the format of MM-dd-yyyy and I am attempting to convert this into a date column.

I tried:

df.select(to_date(df.STRING_COLUMN).alias('new_date')).show()

And I get a string of nulls. Can anyone help?

2

From ChatGPT:

To convert a string column in a PySpark DataFrame with the format “MM-dd-yyyy” into a date column, you can use the to_date function provided by PySpark. Here’s how you can do it:

Assuming you have a DataFrame called df with a string column named date_str in the “MM-dd-yyyy” format, you can convert it to a date column like this:

pythonCopy code

from pyspark.sql.functions import to_date
from pyspark.sql.types import DateType

# Assuming df is your DataFrame and date_str is the string column
df = df.withColumn("date_column", to_date(df["date_str"], "MM-dd-yyyy").cast(DateType()))

In the code above:

  1. We import the necessary functions to_date from pyspark.sql.functions and DateType from pyspark.sql.types.
  2. We use the withColumn method to add a new column called “date_column” to the DataFrame df. This column will contain the converted date values.
  3. We use the to_date function to convert the “date_str” column to a date format. The second argument "MM-dd-yyyy" specifies the format of the input string. Make sure the format string matches your date string format.
  4. We use cast(DateType()) to explicitly cast the result to a DateType to ensure that the column is of the correct data type.

After running this code, your DataFrame df will have a new column “date_column” containing date values. You can then use this column for further processing or analysis.