Code Explanation:
Importing Pandas
import pandas as pd
Purpose: Loads the Pandas library for data manipulation.
Alias pd: This is a standard Python convention so we don’t have to type pandas every time.
Creating the Series
s = pd.Series([50, 40, 30, 20, 10])
Creates a Pandas Series: One-dimensional array-like object with labeled index.
Values: 50, 40, 30, 20, 10
Default Index: 0, 1, 2, 3, 4
Building the Condition
(s >= 20) & (s <= 40)
Step 1: (s >= 20) → [True, True, True, True, False]
Checks if each element is greater than or equal to 20.
Step 2: (s <= 40) → [False, True, True, True, True]
Checks if each element is less than or equal to 40.
Step 3: Combine with & (AND operator):
Result = [False, True, True, True, False]
This means elements at index 1, 2, 3 meet the condition.
Applying the Update
s[(s >= 20) & (s <= 40)] -= 10
Selects the elements that match the condition (40, 30, 20).
Subtracts 10 from each selected value.
Resulting Series:
0 50
1 30
2 20
3 10
4 10
dtype: int64
Calculating the Mean
print(s.mean())
.mean(): Calculates the average of all values.
Calculation: (50 + 30 + 20 + 10 + 10) / 5 = 120 / 5 = 24.0
Output:
24.0
Final Output: 24.0
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