Class 10 AI practical exam questions for 2027, solved the way the exam asks them.

import numpy as np
import statistics

marks = np.array([72, 85, 64, 85, 91, 58, 77])
print("Mean:", round(np.mean(marks), 2))
print("Median:", np.median(marks))
print("Mode:", statistics.mode(marks.tolist()))
above = marks[marks > np.mean(marks)]
print("Above the mean:", above)
print("Count:", above.size)

NumPy has no mode function, which is why statistics is imported. The filter inside the square brackets is the line examiners most like to ask about.

Mean: 76.0
Median: 77.0
Mode: 85
Above the mean: [85 85 91 77]
Count: 4

Check by hand: the total is 532 and 532 / 7 = 76. Sorted, the fourth of seven values is 77.

total = 0
for i in range(3):
    name = input("Name: ")
    score = float(input("Score out of 50: "))
    pct = score / 50 * 100
    total = total + pct
    if pct >= 90:
        grade = "A"
    elif pct >= 75:
        grade = "B"
    elif pct >= 50:
        grade = "C"
    else:
        grade = "Needs support"
    print(name, round(pct, 1), "%", grade)
print("Class average:", round(total / 3, 1), "%")

Riya 92.0 % A
Kabir 77.0 % B
Sana 44.0 % Needs support
Class average: 71.0 %

float(), not int(), because a score such as 38.5 is allowed. The order of the elif tests matters: check 90 before 75.

import pandas as pd

df = pd.read_csv("rainfall.csv")
print(df.shape)
print(df.head(3))
print("Average rainfall:", round(df["rain_mm"].mean(), 1))
wet = df[df["rain_mm"] > 100]
print(wet[["month", "rain_mm"]])

(6, 3)
  month  rain_mm  rainy_days
0   Jun      164           9
1   Jul      238          16
2   Aug      201          14
Average rainfall: 124.8
  month  rain_mm
0   Jun      164
1   Jul      238
2   Aug      201

Our file held Jun 164, Jul 238, Aug 201, Sep 96, Oct 38 and Nov 12. The double square brackets select two columns.

import pandas as pd
import matplotlib.pyplot as plt

df = pd.read_csv("rainfall.csv")
plt.bar(df["month"], df["rain_mm"], color="teal")
plt.axhline(df["rain_mm"].mean(), color="black", linestyle="--")
plt.title("Monthly rainfall, June to November")
plt.xlabel("Month")
plt.ylabel("Rainfall (mm)")
plt.savefig("rainfall.png")
print("Saved rainfall.png")

Saved rainfall.png

# Six teal bars, tallest for Jul (238),
# shortest for Nov (12). The dashed line
# sits at 124.8, crossed only by Jun,
# Jul and Aug.

Call savefig before show, or the saved file can come out blank. In Jupyter, add plt.show() last to see the chart under the cell.