search
Search
Login
Unlock 100+ guides
menu
menu
web
search toc
close
Comments
Log in or sign up
Cancel
Post
account_circle
Profile
exit_to_app
Sign out
What does this mean?
Why is this true?
Give me some examples!
search
keyboard_voice
close
Searching Tips
Search for a recipe:
"Creating a table in MySQL"
Search for an API documentation: "@append"
Search for code: "!dataframe"
Apply a tag filter: "#python"
Useful Shortcuts
/ to open search panel
Esc to close search panel
to navigate between search results
d to clear all current filters
Enter to expand content preview
icon_star
Doc Search
icon_star
Code Search Beta
SORRY NOTHING FOUND!
mic
Start speaking...
Voice search is only supported in Safari and Chrome.
Navigate to

Getting earliest and latest date in PySpark DataFrame

schedule Aug 12, 2023
Last updated
local_offer
PySpark
Tags
mode_heat
Master the mathematics behind data science with 100+ top-tier guides
Start your free 7-days trial now!

Getting earliest and latest date for date columns

Consider the following PySpark DataFrame:

import datetime
df = spark.createDataFrame([['Alex', datetime.date(1998,12,16)], ['Bob', datetime.date(1995,5,9)]], ['name', 'birthday'])
df.show()
+----+----------+
|name| birthday|
+----+----------+
|Alex|1998-12-16|
| Bob|1995-05-09|
+----+----------+

Here, birthday is of type date:

root
|-- name: string (nullable = true)
|-- birthday: date (nullable = true)

Use the F.min(~) method to get the earliest date, and use the F.max(~) method to get the latest date:

from pyspark.sql import functions as F

col_earlist_date = F.min('birthday').alias('earliest')
col_latest_date = F.max('birthday').alias('latest')
df_result = df.select(col_earlist_date, col_latest_date)
df_result.show()
+----------+----------+
| earliest| latest|
+----------+----------+
|1995-05-09|1998-12-16|
+----------+----------+

Here, we are using the alias(~) method to assign a label to the PySpark column returned by F.min(~) and F.max(~).

To extract the earliest and latest dates as variables instead of a PySpark DataFrame:

list_rows = df_result.collect()
print(f'Earliest date: {list_rows[0][0]}') # type is datetime.date
print(f'Latest date: {list_rows[0][1]}')
Earliest date: 1995-05-09
Latest date: 1998-12-16

Here, we are using the PySpark DataFrame's collect() method to convert the row into a list of Row object in the driver node:

list_rows = df_result.collect()
list_rows
[Row(earliest=datetime.date(1995, 5, 9), latest=datetime.date(1998, 12, 16))]

Getting earliest and latest date for date string columns

The above solution works when the column is of type date. If you have date strings, then you must first convert the date strings into native dates using the to_date(~) method.

For example, consider the following PySpark DataFrame with some date strings:

df = spark.createDataFrame([['Alex', '1998-12-16'], ['Bob', '1995-5-9']], ['name', 'birthday'])
df.show()
+----+----------+
|name| birthday|
+----+----------+
|Alex|1998-12-16|
| Bob| 1995-5-9|
+----+----------+

We can convert the date strings to native dates using to_date(~):

col_date = F.to_date(df['birthday'], 'yyyy-M-d')
col_earliest = F.min(col_date).alias('earliest')
col_latest = F.max(col_date).alias('latest')
df.select(col_earliest, col_latest).show()
+----------+----------+
| earliest| latest|
+----------+----------+
|1995-05-09|1998-12-16|
+----------+----------+

Here, the second argument of to_date(~) specifies the format of the date string.

robocat
Published by Isshin Inada
Edited by 0 others
Did you find this page useful?
thumb_up
thumb_down
Comment
Citation
Ask a question or leave a feedback...
thumb_up
0
thumb_down
0
chat_bubble_outline
0
settings
Enjoy our search
Hit / to insta-search docs and recipes!