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Data Science Interview Cards: 42 Questions with Examples

By Ravindra Bagale Last updated: 24 October 2026

About these cards

42 Data Science interview cards: 13 Python basics (py01–py13) plus 28 chapter cards (ch01–ch28) and ch65 time-series. Each card has a small Blinkit Maharashtra teaching example. Scan the QR for the full lesson.

Contents

Python basics

Card P1: Python: how do you prove Python is installed and ready for data work?
Card P2: Python: what is a variable, and how do you check its type?
Card P3: Python: what is an f-string and why prefer it to + for text?
Card P4: Python: when do you use a dict instead of a list?
Card P5: Python: how do if, elif and else pick one path?
Card P6: Python: for loop vs while loop — when do you use each?
Card P7: Python: what is a function, and when do you use def and return?
Card P8: Python: ValueError vs TypeError vs KeyError — what do you say?
Card P9: Python: how do you read a CSV with the csv module (no pandas yet)?
Card P10: Python: what is a virtual environment (venv) and why use it?
Card P11: Python: what is a class, and what are self and __init__?
Card P12: NumPy: why use an array instead of a Python list for maths?
Card P13: Python: how do you structure a mini project before pandas?

Data Science chapters

Card 1: What does grain of one row mean in a Blinkit orders table?
Card 2: Why do you use a virtual environment (venv) for data work?
Card 3: List vs dict — when do you use each for Blinkit city data?
Card 4: What is a NumPy array shape for a city × day grid?
Card 5: Series vs DataFrame — what is the difference?
Card 6: How do you filter Blinkit rows with multiple conditions?
Card 7: Explain groupby as split–apply–combine for Blinkit GMV.
Card 8: concat vs merge — when do you use each?
Card 9: How do you handle duplicate Blinkit order lines?
Card 10: How do you parse Indian dd-mm-yyyy dates in pandas?
Card 11: Wide vs long data — when do you melt for Blinkit?
Card 12: What is EDA on a Blinkit Maharashtra extract?
Card 13: Figure vs Axes in matplotlib — what should you say?
Card 14: When do you prefer seaborn over plain matplotlib?
Card 15: Which chart compares Blinkit GMV across cities best?
Card 16: Walk through the Blinkit Maharashtra end-to-end project steps.
Card 17: How should you approach a warm-up Blinkit filter exercise?
Card 18: loc vs iloc — how do you explain them in an interview?
Card 19: Name three pandas essentials you keep on a cheat sheet.
Card 20: Define GMV as used in this Data Science course.
Card 21: For Blinkit order amounts, when do you use mean vs median?
Card 22: When do you export to_excel for a Blinkit manager pack?
Card 23: What is the SettingWithCopy warning in pandas?
Card 24: How do you load a SQL SELECT into a pandas DataFrame?
Card 25: pandas: how do you rank rows, add a running total and a rolling average?
Card 26: Python requests: how do you call an API safely before pandas?
Card 27: Git for data projects: what goes in .gitignore?
Card 28: pandas merge: how do you check a join with indicator=True?
Card 65: Time series: how do you forecast sales with lag features and LinearRegression?

Python basics

Data Science interview card P1: Python: how do you prove Python is installed and ready for data work? — Python basics · Card P1 of 13: Python: how do you prove Python is installed and ready for data work? · Download PNG · Full lesson

Data Science interview card P2: Python: what is a variable, and how do you check its type? — Python basics · Card P2 of 13: Python: what is a variable, and how do you check its type? · Download PNG · Full lesson

Data Science interview card P3: Python: what is an f-string and why prefer it to + for text? — Python basics · Card P3 of 13: Python: what is an f-string and why prefer it to + for text? · Download PNG · Full lesson

Data Science interview card P4: Python: when do you use a dict instead of a list? — Python basics · Card P4 of 13: Python: when do you use a dict instead of a list? · Download PNG · Full lesson

Data Science interview card P5: Python: how do if, elif and else pick one path? — Python basics · Card P5 of 13: Python: how do if, elif and else pick one path? · Download PNG · Full lesson

Data Science interview card P6: Python: for loop vs while loop — when do you use each? — Python basics · Card P6 of 13: Python: for loop vs while loop — when do you use each? · Download PNG · Full lesson

Data Science interview card P7: Python: what is a function, and when do you use def and return? — Python basics · Card P7 of 13: Python: what is a function, and when do you use def and return? · Download PNG · Full lesson

Data Science interview card P8: Python: ValueError vs TypeError vs KeyError — what do you say? — Python basics · Card P8 of 13: Python: ValueError vs TypeError vs KeyError — what do you say? · Download PNG · Full lesson

Data Science interview card P9: Python: how do you read a CSV with the csv module (no pandas yet)? — Python basics · Card P9 of 13: Python: how do you read a CSV with the csv module (no pandas yet)? · Download PNG · Full lesson

Data Science interview card P10: Python: what is a virtual environment (venv) and why use it? — Python basics · Card P10 of 13: Python: what is a virtual environment (venv) and why use it? · Download PNG · Full lesson

Data Science interview card P11: Python: what is a class, and what are self and __init__? — Python basics · Card P11 of 13: Python: what is a class, and what are self and __init__? · Download PNG · Full lesson

Data Science interview card P12: NumPy: why use an array instead of a Python list for maths? — Python basics · Card P12 of 13: NumPy: why use an array instead of a Python list for maths? · Download PNG · Full lesson

Data Science interview card P13: Python: how do you structure a mini project before pandas? — Python basics · Card P13 of 13: Python: how do you structure a mini project before pandas? · Download PNG · Full lesson

Data Science chapters

Data Science interview card 1: What does grain of one row mean in a Blinkit orders table? — Card 1 of 28: What does grain of one row mean in a Blinkit orders table? · Download PNG · Full lesson

Data Science interview card 2: Why do you use a virtual environment (venv) for data work? — Card 2 of 28: Why do you use a virtual environment (venv) for data work? · Download PNG · Full lesson

Data Science interview card 3: List vs dict — when do you use each for Blinkit city data? — Card 3 of 28: List vs dict — when do you use each for Blinkit city data? · Download PNG · Full lesson

Data Science interview card 4: What is a NumPy array shape for a city × day grid? — Card 4 of 28: What is a NumPy array shape for a city × day grid? · Download PNG · Full lesson

Data Science interview card 5: Series vs DataFrame — what is the difference? — Card 5 of 28: Series vs DataFrame — what is the difference? · Download PNG · Full lesson

Data Science interview card 6: How do you filter Blinkit rows with multiple conditions? — Card 6 of 28: How do you filter Blinkit rows with multiple conditions? · Download PNG · Full lesson

Data Science interview card 7: Explain groupby as split–apply–combine for Blinkit GMV. — Card 7 of 28: Explain groupby as split–apply–combine for Blinkit GMV. · Download PNG · Full lesson

Data Science interview card 8: concat vs merge — when do you use each? — Card 8 of 28: concat vs merge — when do you use each? · Download PNG · Full lesson

Data Science interview card 9: How do you handle duplicate Blinkit order lines? — Card 9 of 28: How do you handle duplicate Blinkit order lines? · Download PNG · Full lesson

Data Science interview card 10: How do you parse Indian dd-mm-yyyy dates in pandas? — Card 10 of 28: How do you parse Indian dd-mm-yyyy dates in pandas? · Download PNG · Full lesson

Data Science interview card 11: Wide vs long data — when do you melt for Blinkit? — Card 11 of 28: Wide vs long data — when do you melt for Blinkit? · Download PNG · Full lesson

Data Science interview card 12: What is EDA on a Blinkit Maharashtra extract? — Card 12 of 28: What is EDA on a Blinkit Maharashtra extract? · Download PNG · Full lesson

Data Science interview card 13: Figure vs Axes in matplotlib — what should you say? — Card 13 of 28: Figure vs Axes in matplotlib — what should you say? · Download PNG · Full lesson

Data Science interview card 14: When do you prefer seaborn over plain matplotlib? — Card 14 of 28: When do you prefer seaborn over plain matplotlib? · Download PNG · Full lesson

Data Science interview card 15: Which chart compares Blinkit GMV across cities best? — Card 15 of 28: Which chart compares Blinkit GMV across cities best? · Download PNG · Full lesson

Data Science interview card 16: Walk through the Blinkit Maharashtra end-to-end project steps. — Card 16 of 28: Walk through the Blinkit Maharashtra end-to-end project steps. · Download PNG · Full lesson

Data Science interview card 17: How should you approach a warm-up Blinkit filter exercise? — Card 17 of 28: How should you approach a warm-up Blinkit filter exercise? · Download PNG · Full lesson

Data Science interview card 18: loc vs iloc — how do you explain them in an interview? — Card 18 of 28: loc vs iloc — how do you explain them in an interview? · Download PNG · Full lesson

Data Science interview card 19: Name three pandas essentials you keep on a cheat sheet. — Card 19 of 28: Name three pandas essentials you keep on a cheat sheet. · Download PNG · Full lesson

Data Science interview card 20: Define GMV as used in this Data Science course. — Card 20 of 28: Define GMV as used in this Data Science course. · Download PNG · Full lesson

Data Science interview card 21: For Blinkit order amounts, when do you use mean vs median? — Card 21 of 28: For Blinkit order amounts, when do you use mean vs median? · Download PNG · Full lesson

Data Science interview card 22: When do you export to_excel for a Blinkit manager pack? — Card 22 of 28: When do you export to_excel for a Blinkit manager pack? · Download PNG · Full lesson

Data Science interview card 23: What is the SettingWithCopy warning in pandas? — Card 23 of 28: What is the SettingWithCopy warning in pandas? · Download PNG · Full lesson

Data Science interview card 24: How do you load a SQL SELECT into a pandas DataFrame? — Card 24 of 28: How do you load a SQL SELECT into a pandas DataFrame? · Download PNG · Full lesson

Data Science interview card 25: pandas: how do you rank rows, add a running total and a rolling average? — Card 25 of 28: pandas: how do you rank rows, add a running total and a rolling average? · Download PNG · Full lesson

Data Science interview card 26: Python requests: how do you call an API safely before pandas? — Card 26 of 28: Python requests: how do you call an API safely before pandas? · Download PNG · Full lesson

Data Science interview card 27: Git for data projects: what goes in .gitignore? — Card 27 of 28: Git for data projects: what goes in .gitignore? · Download PNG · Full lesson

Data Science interview card 28: pandas merge: how do you check a join with indicator=True? — Card 41 of 28: pandas merge: how do you check a join with indicator=True? · Download PNG · Full lesson

Data Science interview card 65: Time series: how do you forecast sales with lag features and LinearRegression? — Card 65 · ch65 time series: Time series: how do you forecast sales with lag features and LinearRegression? · Download PNG · Full lesson