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Can you help me solve this please
[enter image description here[[[[enter image description here](https://i.stack.imgur.com/utguF.jpg)](https://i.stack.imgur.com/dd6gE.jpg)](https://i.stack.imgur.com/nf3KN.jpg)](https://i.stack.imgur.com/1nfxb.jpg)](https://i.stack.imgur.com/ebSIl.jpg)
I tried everything..
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I want to train a model using RandomForestClassifier but there are infinite values in my data
How can I handle infinite values in the pipeline before the algorithm?
Can anyone help me?
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It is the question given by my python teacher and IM trying to solve them from several hours
Im expecting the answer as whether im give other numbers except from given numbers in the ishould get the correct answer
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OpCo_code = spark.sql(f""" SELECT OPCOCode
FROM delta./{SALES_ORG_REFERENCE_OBJECT}
WHERE SalesOrganisationCode = "{SalesOrg_row['SalesOrganisationCode']}" AND RegionID ="{SalesOrg_row['RegionID']}" """).collect()[0][0]
Output: HP
I am unable to pick the data in column(OPCOCode) uniform multiple rows.
I am expecting output
HP, IC,UF
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the corresponding pattern is ('Handmade Frozen Car', 11.0). I want to get the value as 11.0. Any suggestions are highly appreciated.
x = ('Handmade Frozen Car', 11.0)
secondElement = x[1]
secondElement will be equal to 11.0
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How would I use the dataset at http://oceancolor.gsfc.nasa.gov/DOCS/DistFromCoast/ to efficiently determine the distance of a given coordinate (lat,lng) to the nearest coastline?
It's quite a large file. Is there a library that can help with processing this kind of data?