✅Python Interview Questions with Answers 🧑‍💻👩‍💻

1️⃣ Write a function to remove outliers from a list using IQR.

import numpy as np

def remove_outliers(data):
    q1 = np.percentile(data, 25)
    q3 = np.percentile(data, 75)
    iqr = q3 - q1
    lower = q1 - 1.5 * iqr
    upper = q3 + 1.5 * iqr
    return [x for x in data if lower <= x <= upper]

2️⃣ Convert a nested list to a flat list.

nested = [[1, 2], [3, 4],]
flat = [item for sublist in nested for item in sublist]

3️⃣ Read a CSV file and count rows with nulls.

import pandas as pd

df = pd.read_csv('data.csv')
null_rows = df.isnull().any(axis=1).sum()
print("Rows with nulls:", null_rows)

4️⃣ How do you handle missing data in pandas?
⦁ Drop missing rows: df.dropna()
⦁ Fill missing values: df.fillna(value)
⦁ Check missing data: df.isnull().sum()

5️⃣ Explain the difference between loc[] and iloc[].
⦁ loc[]: Label-based indexing (e.g., row/column names)
Example: df.loc[0, 'Name']
⦁ iloc[]: Position-based indexing (e.g., row/column numbers)
Example: df.iloc

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