Yara International Data Analyst Interview Questions and Answers

Q1. Only technical discussion
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Q1. Only technical discussion on data models, AWS and sparks
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Q1. Explain logistic regression
Ans. 
Logistic regression is a statistical model used to predict the probability of a binary outcome based on one or more predictor variables.
• Logistic regression is a type of regression analysis used when the dependent variable is categorical or binary.

• It estimates the probability of the outcome using a logistic function.

• The model calculates the odds of the outcome and transforms them into probabilities.

• It uses a logit link ...read more
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Q1. Basic questions regarding ANOVA, Regression, Classification, Design of Experiments
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Q2. Practical questions for computer vision project that I did in my PhD
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Q1. Regarding Relocation
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Q2. Can't remember much It's long time
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It was a website-based test and some average type questions

Advanced Python skills is required to clear the interview

Q1. What is pandas?
Ans. 
pandas is a Python library used for data manipulation and analysis.
• pandas provides data structures like DataFrame and Series for working with structured data

• It offers tools for cleaning, transforming, and analyzing data

• pandas can handle various data formats like CSV, Excel, SQL databases, and more
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Q2. While webscraping, do HTML tables also get extracted?
Ans. 
Yes, HTML tables can be extracted while webscraping.
• HTML tables can be extracted using libraries like BeautifulSoup in Python.

• The data from the HTML tables can be converted into a structured format like CSV or Excel.

• Webscraping tools like Octoparse and Import.io can also extract HTML tables.

• Regular expressions can be used to extract specific data from HTML tables.
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Q1. Past experience
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Q2. Plan for sale in future
Ans. 
To plan for future sales, I will analyze market trends, set realistic goals, train my team, and focus on customer satisfaction.
• Analyze market trends to identify opportunities and threats

• Set realistic sales goals based on market analysis

• Train sales team on new products, techniques, and customer service

• Focus on customer satisfaction to build long-term relationships and repeat business
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