Python Interview Questions for Data Analysts 2026

Q1: What is the difference between a list and a tuple in Python?
A: List: mutable (can change after creation), uses []
   Tuple: immutable (cannot change), uses ()
   Use tuple for fixed data (coordinates, RGB values)
   Use list for data that changes (column names, values)

Q2: What is pandas and what is it used for?
A: pandas is a Python library for tabular data — loading,
   cleaning, filtering, grouping, and analysing DataFrames.
   Think of it as Excel functionality inside Python.

Q3: What is the difference between loc and iloc?
A: loc: label-based — use column names and index labels
   iloc: integer position-based — use numbers 0,1,2...
   loc[0:4] includes row 4; iloc[0:4] excludes row 4.

Q4: How do you handle missing values in pandas?
A: df.isnull().sum() — count nulls per column
   df.dropna() — remove rows with any null
   df.fillna(value) — fill with a specific value (mean, median, "Unknown")
   Choice depends on: % of nulls, column type, business context

Q5: What is the difference between apply() and map()?
A: .apply() — works on Series or DataFrame (rows or cols)
   .map() — works on Series only, element by element
   Both apply a function to each element; apply() is more flexible

Q6: How do you merge two DataFrames on a key column?
A: pd.merge(df1, df2, on="CustomerID", how="left")
   how: "inner" (default), "left", "right", "outer"
   left join = all rows from left, matched from right

Q7: What is groupby and how do you use it?
A: df.groupby("Region")["Revenue"].sum()
   Multiple aggregations:
   df.groupby("Region").agg(Total=("Revenue","sum"),
                             Count=("OrderID","count"))

Q8: Write code to find duplicate rows in a DataFrame.
A: df.duplicated().sum()          # count duplicates
   df[df.duplicated()]            # show duplicate rows
   df.drop_duplicates(inplace=True)  # remove them

Q9: How do you convert a column of "₹75,000" strings to int?
A: df["Salary"] = (df["Salary"]
     .str.replace("₹","")
     .str.replace(",","")
     .str.strip()
     .astype(int))

Q10: What is the difference between .copy() and assignment?
A: df2 = df           → df2 is a VIEW — changes affect df too
   df2 = df.copy()    → df2 is independent — changes are isolated
   Always use .copy() when you want a separate working copy