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10+ Weikfield Foods Interview Questions and Answers

Updated 22 Feb 2024
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Q1. Print rows where a certain criterion is met (ex - in a dataset of employees select the ones whose salary is greater than 100000 - in SQL)

Ans.

Use SQL SELECT statement with WHERE clause to filter rows based on a specific criterion.

  • Use SELECT statement with WHERE clause to specify the criterion (ex: salary > 100000)

  • Example: SELECT * FROM employees WHERE salary > 100000;

  • Ensure proper syntax and column names are used in the query

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Q2. Extract only India Players from dictionary (using list comprehension) CSK = {"Dhoni" : "India", "Du Plessis" : "South Africa", "RituRaj": "India", "Peterson" : "England", "Lara" : "West Indies"}

Ans.

Extract India players from a dictionary using list comprehension

  • Use list comprehension to filter out players with nationality as 'India'

  • Create a new list with only the India players

  • Example: [player for player, nationality in CSK.items() if nationality == 'India']

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Q3. What are the types of regression models, name them and explain them

Ans.

Types of regression models include linear regression, logistic regression, polynomial regression, ridge regression, and lasso regression.

  • Linear regression: used to model the relationship between a dependent variable and one or more independent variables.

  • Logistic regression: used for binary classification problems, where the output is a probability value between 0 and 1.

  • Polynomial regression: fits a curve to the data by adding polynomial terms to the linear regression model.

  • Ri...read more

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Q4. What is ETL and what are the types or examples of ETL tools

Ans.

ETL stands for Extract, Transform, Load. It is a process of extracting data from various sources, transforming it into a usable format, and loading it into a target database.

  • ETL tools include Informatica PowerCenter, Talend, Apache Nifi, Microsoft SQL Server Integration Services (SSIS), and IBM InfoSphere DataStage.

  • Extract: Data is extracted from various sources such as databases, files, APIs, etc.

  • Transform: Data is cleaned, validated, and transformed into a format suitable f...read more

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Q5. How do you print the 3, 5 and 7th row in a database (Python - use Pandas)

Ans.

Printing specific rows from a database using Pandas in Python

  • Use Pandas library to read the database into a DataFrame

  • Use iloc method to select specific rows by index

  • Print the selected rows

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Q6. Find Common Elements in three lists using sets arr1 = [1,5,10,20,40,80,100] arr2 = [6,7,20,80,100] arr3 = [3,4,15,20,30,70,80,120]

Ans.

Use sets to find common elements in three lists.

  • Convert the lists to sets for efficient comparison.

  • Use the intersection method to find common elements.

  • Return the common elements as a set or list.

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Q7. Print rows with the same set of values in column (these are not duplicates row - just the duplicates values in a column)

Ans.

Print rows with the same set of values in a column

  • Identify unique sets of values in the column

  • Group rows based on these unique sets of values

  • Print out the rows for each unique set of values

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Q8. Print Unique values in the dataset and delete the duplicate rows (SQL)

Ans.

Use DISTINCT keyword to print unique values and DELETE with a subquery to remove duplicate rows.

  • Use SELECT DISTINCT column_name FROM table_name to print unique values.

  • Use DELETE FROM table_name WHERE row_id NOT IN (SELECT MAX(row_id) FROM table_name GROUP BY column_name) to delete duplicate rows.

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Q9. Print rows with the second highest criterion value without using offset function in SQL

Ans.

Use subquery to find rows with second highest criterion value in SQL without using offset function.

  • Use a subquery to find the maximum criterion value

  • Then use another subquery to find the maximum value that is less than the maximum value found in the first subquery

  • Finally, select rows with the second highest criterion value

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Q10. Split Dataset in train, test and validation (import library and split dataset)

Ans.

Use scikit-learn library to split dataset into train, test, and validation sets

  • Import train_test_split from sklearn.model_selection

  • Specify test_size and validation_size when splitting the dataset

  • Example: X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

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Q11. Difference in Linear and Logistic Regression

Ans.

Linear regression is used for continuous variables, while logistic regression is used for binary outcomes.

  • Linear regression predicts continuous outcomes, while logistic regression predicts binary outcomes.

  • Linear regression uses a linear equation to model the relationship between the independent and dependent variables.

  • Logistic regression uses the logistic function to model the probability of a binary outcome.

  • Linear regression is used for tasks like predicting house prices, wh...read more

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Q12. Difference in Random Forest and Decision Tree

Ans.

Random Forest is an ensemble method using multiple decision trees, while Decision Tree is a single tree-based model.

  • Random Forest is a collection of decision trees that are trained on random subsets of the data.

  • Decision Tree is a single tree structure that makes decisions by splitting the data based on features.

  • Random Forest reduces overfitting by averaging the predictions of multiple trees.

  • Decision Tree can be prone to overfitting due to its high complexity.

  • Random Forest is ...read more

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Q13. Difference between Power BI and Tableau

Ans.

Power BI is a Microsoft product focused on business intelligence and data visualization, while Tableau is a standalone data visualization tool.

  • Power BI is more user-friendly and integrates well with other Microsoft products.

  • Tableau is known for its powerful data visualization capabilities and flexibility in creating complex visualizations.

  • Power BI is often preferred by organizations already using Microsoft products, while Tableau is popular among data analysts and visualizati...read more

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Q14. Limitations of Power BI and Tableau

Ans.

Power BI and Tableau have limitations in terms of data connectivity, customization, and pricing.

  • Limited data connectivity options compared to other tools

  • Limited customization capabilities for advanced analytics

  • High pricing for enterprise-level features

  • Tableau has better visualization capabilities but can be more complex to use

  • Power BI is more user-friendly but may lack certain advanced features

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