DataScience Judge


DS Judge environment

Supported languages

Language Version
Python 3 3.5.2
R 4.0.3

Legend

Legend Explanation
NameError Name Error
KeyError Key Error
AttributeError Attribute Error
TLE Time Limit Error
ModuleNotFoundError Module Not Found Error
ImportError Import Error
FileNotFoundError File Not Found Error
ValueError Value Error
MLE Memory Limit Error

Is there any restriction on the type of programming language that I can use in the Jupyter notebook?

The Jupyter notebook supports Python 3.5.2.

How are the data science problems evaluated? Evaluation is based on the evaluation metrics that are defined in the problem statement.

What are train and test data? In a dataset, a training set is implemented to build up a model, while a test set is to validate the model built. Data points in the training set are excluded from the test set.

Which libraries and packages can I use for building my models?

HackerEarth’s data science interface supports the packages and versions that are listed here.

How should I access the test and train datasets in the code editor?

To access files in the code editor in Python 3

import pandas as pd

train = pd.read_csv('dataset/train.csv')

test = pd.read_csv('dataset/test.csv')

To access files in the code editor in R

library(readr)

train <- read_csv("dataset/train.csv")

test <- read_csv("dataset/test.csv")

What is the significance of the memory limit?

The evaluation of each compilation and submission is limited to a certain memory. If your code exceeds this memory limit, then you are required to optimize your code.

What is the significance of the time limit?

The evaluation of each compilation and submission is limited to a certain period of time. If your code takes longer than the permitted execution time, then you are required to optimize the code.

What is the difference between Compile & test and Submit?

Compile & test is used to evaluate your code against the sample dataset whereas Submit is used to evaluate your code against the complete dataset.

In which format should I submit my final submission file?

You are required to submit your predictions in a ‘.csv’ file named ‘submission.csv’.

How should I make my submission in the code editor?

It is mandatory to write your submission (data frame) into the submission.csv file. The submission files contain the predictions. This can be performed as follows:

Python 3

submission.to_csv('submission.csv',index = False)

R

write.table(submission,file = "submission.csv",row.names = FALSE,sep=",")

Where can I view my submissions?

You can view your submissions in the All Submissions section of the challenge page.

Do I have the write permission to the current working directory?

You do not have the write permission to the directory. You only have the read permission.

Can I view other's solutions?

No, you can not. Similarly, no one can view your solution.

Dos and don’ts in the comment section

While posting comments on the bottom of the problem’s page, please keep the following things in mind:

  • Do not spam.
  • Do not post any source code.
  • Admins/moderators are allowed to delete the comments.

If all this still doesn't answer your question, drop us an email at support@hackerearth.com.


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