Interview Q&A / Data Science

1. How do you detect outliers using the IQR and z-score methods?

   With the IQR method, a value is an outlier if it lies below Q1 minus 1.5 times the IQR or above Q3 plus 1.5 times the IQR. With the z-score method, a value is flagged if it is more than about 3 standard deviations from the mean. IQR is more robust for skewed data and small samples, because outliers inflate the mean and standard deviation.

   IntermediateIn-depth4 min read
2. How do you handle missing values in a dataset?

   First find how much is missing and why. Then either drop rows or columns (when little is missing or a column is mostly empty) or fill the gaps, using the median for skewed numbers, the mode for categories, forward fill for time series, or a model-based method. Often add a flag column that records which values were missing.

   IntermediateIn-depth4 min read
3. How do you find and handle missing values in pandas?

   Use isna().sum() to count them, then dropna to remove rows or columns, or fillna to fill them with a constant, mean, median or group value. Check what share is missing first, since the right fix depends on it.

   BeginnerQuick answer1 min read