Tip 1 : Have in-depth knowledge of data-frame manipulation using Pandas
Tip 2 : Learn all NumPy array methods
Tip 3 : Good working knowledge about Scikit Learn
Tip 1 : Have 2-3 good projects on Machine Learning or Data Science preferably in Python.
Tip 2 : List only those skills which you are good at.
The test is divided into 3 sections:
1. R coding.
2. Python coding. This section includes NumPy and scikit questions.
3. Statistics. This section includes T-tests, Anova regression distributions, and chi-square.
Each section has roughly 12 questions. The number of questions and difficulty is not set in advance, the test is adaptive. The more correct answers you give, the more the questions get tougher. The qualification does not depend upon the number of questions solved, rather on the difficulty level you can achive.
Complete the function to find the value in a specified categorical column with the highest average of a specified numeric column.
import pandas as pddef category_avg(df, cat_column, num_column):
#### write code here solution = None
return solutiontest_case = category_avg(price_df, 'city','price')



For given 2D array :
[ [ 1, 2, 3 ],
[ 4, 5, 6 ],
[ 7, 8, 9 ] ]
After 90 degree rotation in anti clockwise direction, it will become:
[ [ 3, 6, 9 ],
[ 2, 5, 8 ],
[ 1, 4, 7 ] ]
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