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I applied via Company Website and was interviewed before Aug 2020. There were 3 interview rounds.
Top trending discussions
I applied via Campus Placement and was interviewed in Oct 2022. There were 4 interview rounds.
1 easy sql and 1 easy python for 55 min
1 easy python and very hard sql for 1 hr 50 min
Answering a question on writing a join and implementing left join using pandas for Data Analyst role.
To write a join, we need to identify the common column(s) between two tables and use the JOIN keyword in SQL.
Example: SELECT * FROM table1 JOIN table2 ON table1.common_column = table2.common_column
To implement left join using pandas, we can use the merge() function with how='left' parameter.
Example: pd.merge(table1, tab
I applied via Naukri.com
I applied via Naukri.com and was interviewed before Feb 2022. There were 4 interview rounds.
Basic aptitude questions of quant and reasoning and general english
Case study of varies products asked around 15-20 which were easy to attempt
SQL is a programming language used for managing and manipulating relational databases. Excel formulas are used for performing calculations and data analysis in Microsoft Excel.
SQL is used to retrieve, insert, update, and delete data from databases.
Excel formulas are written using functions and operators to perform calculations and manipulate data.
SQL example: SELECT * FROM customers WHERE age > 30;
Excel formula example...
I applied via Referral and was interviewed in Jun 2022. There were 3 interview rounds.
Normal aptitude questions
I applied via Naukri.com and was interviewed before May 2023. There were 2 interview rounds.
There will be MCQ Questions. They will ask you to use internet and answer the questions.
They want to check your research skills.
Aptitude test of 30 min is conducted
I applied via Referral and was interviewed before Mar 2022. There were 3 interview rounds.
Basic coding questions And logical questions
Simple program for mathematics
I applied via Referral and was interviewed before Feb 2023. There were 2 interview rounds.
Linear regression assumptions include linearity, independence, homoscedasticity, and normality.
Linearity: The relationship between the independent and dependent variables is linear.
Independence: The residuals are independent of each other.
Homoscedasticity: The variance of the residuals is constant across all levels of the independent variables.
Normality: The residuals are normally distributed.
Example: If we are predict...
Multicollinearity is a phenomenon in which two or more predictor variables in a regression model are highly correlated.
Multicollinearity can lead to unstable estimates of the coefficients and make it difficult to determine the effect of each predictor variable on the outcome.
One way to tackle multicollinearity is to identify the highly correlated variables and consider removing one of them from the model.
Another approa...
Time series analysis components include trend, seasonality, cyclicality, and irregularity.
Trend: Long-term movement or direction of the data.
Seasonality: Regular patterns that occur at specific intervals.
Cyclicality: Repeating patterns that are not necessarily at fixed intervals.
Irregularity: Random fluctuations or noise in the data.
Examples: Trend in stock prices, seasonality in retail sales, cyclicality in economic c
Preventive measures for regression assumptions not met
Check for multicollinearity among independent variables
Transform variables if they are not normally distributed
Consider using non-parametric regression methods
Use robust regression techniques to handle outliers
Collect more data to improve model performance
Handling missing values is crucial in data analysis. Various techniques like imputation, deletion, or prediction can be used.
Use imputation techniques like mean, median, mode to fill in missing values.
Consider using predictive modeling to estimate missing values based on other variables.
Delete rows or columns with a high percentage of missing values if they cannot be accurately imputed.
Use advanced techniques like K-ne...
Tuple is immutable and fixed in size, while list is mutable and can change in size.
Tuple is created using parentheses, while list is created using square brackets.
Tuple elements can be of different data types, while list elements are usually of the same data type.
Tuple is faster than list for iteration and accessing elements.
Example: tuple = (1, 'a', True), list = [1, 2, 3]
Outliers can be detected using statistical methods like Z-score, IQR, or visualization techniques like box plots.
Calculate Z-score for each data point and identify points with Z-score greater than a certain threshold (usually 3 or -3).
Use Interquartile Range (IQR) to identify outliers by determining data points that fall below Q1 - 1.5 * IQR or above Q3 + 1.5 * IQR.
Visualize the data using box plots and identify points...
I applied via LinkedIn and was interviewed before Mar 2023. There were 3 interview rounds.
Written test covering economic questions
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Defence Research & Development Organisation
Nielsen Holdings
Kantar
GfK MODE