{}
import pandas as pd
# Creating the dataset
data = {'Scores': [85, 90, 70, 90, 80, 100, 60, 65]}
df = pd.DataFrame(data)
# 1. Calculating individual statistics
print(f"Mean: {df['Scores'].mean()}")
print(f"Median: {df['Scores'].median()}")
print(f"Mode: {df['Scores'].mode()[0]}") # Mode returns a Series, so we take the first index
print(f"Variance: {df['Scores'].var(ddof=0)}") # ddof=0 for population variance
print(f"Std Deviation: {df['Scores'].std(ddof=0)}")
print("-" * 30)
# 2. The "Data Scientist way" (Get all at once)
print("Summary Statistics:")
print(df['Scores'].describe())