I am ingesting data from a excel spreadsheet. Half the date has a date format the other half has a excel numerical value (e.g. 44834 = 30/09/2022)
How do you run through the data and standardise the date format.
df.withColumn("Changed_date", when(to_date(f.col("applicationdate"), "MM/dd/yyyy").isNotNull(), to_date(f.col("applicationdate"), "MM/dd/yyyy"))
.when(f.expr("date_add('1899-12-31', cast(applicationdate as int)").isNotNull(),f.expr("date_add('1899-12-31', cast(applicationdate as int)")).otherwise( to_date("1899-12-31", "MM-dd-yyyy")))
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My Google Sheets is currently set to UK London GMT
I have some data that is needed in UK format and other data that is needed in US format within the same sheet.
I'm using date time as dd-mm-yyyy hh:mm:ss and have been trying to convert this to US yyyy-mm-dd hh:mm:ss
When formatting the UK date time to as text and using this formula
=ARRAYFORMULA(REGEXREPLACE(A2:A, "(\d{4})-(\d+)-(\d+)", "$3/$2/$1"))
It should be converting for me however is stays the same.
I have also tried simply copying and pasting in a new column with the intention of changing format from within formatting settings but when pasting it seems to randomly select different formats in some rows using / instead of - and in other rows returning a number instead of date time.
How can I get this to work correctly?
try:
=TEXT(A2, "e-m-d h:mm:ss")
In Aws Glue after extracting data in DynamicFrame I'm converting date time format to UTC, But if in case date format is wrong for eg Invalid value for date, It will break entire glue flow.
So I want to Filter out these bad data from DynamicFrame before processing it further.
I'm using Filter.apply for filtering data and my date is present in "Date": "2022-01-01T12:11:27.251Z" this format.
You can parse the Date field to check if it has the expected format. Example:
from datetime import datetime
date_str = "2022-01-01T12:11:27.251Z"
try:
datetime_obj = datetime.strptime(date_str, "%Y-%m-%dT%H:%M:%S.%fZ")
# date_str has the correct format, continue processing row
except ValueError:
# date_str does not have the correct format, do something...
You can include this logic in the implementation of Filter.apply(). For example, if the Date field has an invalid format, the row can be filtered out.
I'm working with a large CSV file with millions of rows. I'm using OpenRefine to manipulate this large data set.
I have a column with date strings in this format "2017-08-17 04:36:00". And I would like to convert them to Unix time in integer format like 1502944560.
I see many Q&A on converting Unix time to Date String but not the other way around. Is this possible in OpenRefine?
value.toDate().datePart("time")
(see the bottom of this documentation for other conversion strings)
Coming out of an Oracle background converting dates from any format to any format is really easy.
How is this done in SQLite? I've searched and searched for answers and most of the answers simply say... Save your date/strings in SQLite in one single format which is YYYY-MM-DD HH:MM:SS.SSS. This seems rigid to me.
I don't have that luxury as my data is stored in this format DD/MM/YYYY HH:MI:SS am ex. 3/7/2020 8:02:31 AM.
NOTE: For single days/months my date values do not contain leading zeros and my time is NOT in military time.
How do I tell SQLite what my date format is so that I can correctly convert my stored dates to SQLite datetime formats?
Convert from SQLite Date Format to Oracle Date Example:
In Oracle I would simply use the to_date function like so
to_date('2019-03-07 15:39:34', 'YYYY-MM-DD HH24:MI:SS')
All one needs to do is to tell the function what the date format is... and then it spits out a date.... easy peasy. What this example does is convert a SQLite date formated string to a date that Oracle recognizes as a date. It doesn't matter what the format is in as I tell the function what format to expect.
How do I Convert Dates in SQLite from any format to the SQLite Format?
Converting from SQLite's date format string to ANY date is easy as there are functions built in that do this easily... but how to do this the other way round?
while converting from csv to parquet, using AWS glue ETL job following mapped fields in csv read as string to date and time type.
this is the actual csv file
after mapping and converting, date filed is empty and time is concatenated with today's date
How to convert with proper date and time format?
It uses presto datatypes so data should be in correct format
DATE Calendar date (year, month, day).
Example: DATE '2001-08-22'
TIME Time of day (hour, minute, second, millisecond) without a time
zone. Values of this type are parsed and rendered in the session time
zone.
Example: TIME '01:02:03.456'
TIMESTAMP Instant in time that includes the date and time of day
without a time zone. Values of this type are parsed and rendered in
the session time zone.
Example: TIMESTAMP '2001-08-22 03:04:05.321'
You may use:
from pyspark.sql.functions import to_timestamp, to_date, date_format
df = df.withColumn(col, to_timestamp(col, 'dd-MM-yyyy HH:mm'))
df = df.withColumn(col, to_date(col, 'dd-MM-yyyy'))
df = df.withColumn(col, date_format(col, 'HH:mm:ss'))