day 3 | consecutive days | pyspark scenario based interview questions and answers

day 3
consecutive days
pyspark scenario based interview questions and answers
Create DataFrame Code :
====================
data = [
(1, '2024-03-01'),
(1, '2024-03-02'),
(1, '2024-03-03'),
(1, '2024-03-04'),
(1, '2024-03-06'),
(1, '2024-03-10'),
(1, '2024-03-11'),
(1, '2024-03-12'),
(1, '2024-03-13'),
(1, '2024-03-14'),
(1, '2024-03-20'),
(1, '2024-03-25'),
(1, '2024-03-26'),
(1, '2024-03-27'),
(1, '2024-03-28'),
(1, '2024-03-29'),
(1, '2024-03-30'),
(2, '2024-03-01'),
(2, '2024-03-02'),
(2, '2024-03-03'),
(2, '2024-03-04'),
(3, '2024-03-01'),
(3, '2024-03-02'),
(3, '2024-03-03'),
(3, '2024-03-04'),
(3, '2024-03-04'),
(3, '2024-03-04'),
(3, '2024-03-05'),
(4, '2024-03-01'),
(4, '2024-03-02'),
(4, '2024-03-03'),
(4, '2024-03-04'),
(4, '2024-03-04')
]
schema = "user_id int , login_date string"
df = spark.createDataFrame(data = data , schema = schema)
df.display()
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[@VikasChavan-v1c]

Great work brother, keep it up

[@karthickraja1026]

Amazing brother 💥 I learned lot from your channel. Keep rocking 💯

[@punpompur]

One good thing about this series is that you share the dataframes directly which makes it quite easy to start with coding directly. Quite helpful

[@pradumanyadav493]

Excellent series sir , please don't stop it

[@dhanushkumar7849]

Very good explanation Man

[@KapilKumar-hk9xk]

Amazing

[@DEwithDhairy]

Thanks 😄

[@punpompur]

Does it matter if we use row_number or dense_rank? I tried the code with row_number and the output matched the expected result