Creating Series

What is a Series?

A pandas Series is a one-dimensional labeled array. Think of it as a single column from a spreadsheet, each value has a label (the index) and the data can be any type: integers, floats, strings, or even Python objects.

import pandas as pd

scores = pd.Series([88, 92, 75, 81])
print(scores)

Output:

0    88
1    92
2    75
3    81
dtype: int64

The left column is the index (0, 1, 2, 3 by default). The right column is the data. Together they form a Series.

Creating Series from different sources

From a list, the index defaults to a range of integers:

temperatures = pd.Series([22.5, 24.1, 19.8, 26.3])
print(temperatures)

From a dictionary, the keys become the index:

population = pd.Series({
    "Lagos": 15_400_000,
    "Cairo": 20_900_000,
    "Johannesburg": 5_600_000,
})
print(population)

Output:

Lagos           15400000
Cairo           20900000
Johannesburg     5600000
dtype: int64

From a scalar, a single value is repeated to fill the index:

zeros = pd.Series(0, index=["a", "b", "c", "d"])
print(zeros)

Accessing values

Use the index to retrieve values. With a labeled index, you can use bracket notation or dot access:

print(population["Cairo"])           # 20900000
print(population[["Lagos", "Johannesburg"]])  # subset with multiple labels

With an integer index, you can slice like a list:

print(scores[1:3])   # select index 1 and 2

Vectorized operations

Series support element-wise operations without loops:

celsius = pd.Series([22, 25, 18, 30])
fahrenheit = celsius * 9 / 5 + 32
print(fahrenheit)

Output:

0    71.6
1    77.0
2    64.4
3    86.0
dtype: float64

Comparison operators return a boolean Series:

print(celsius > 24)

Output:

0    False
1     True
2    False
3     True
dtype: bool

Useful Series attributes and methods

print(scores.mean())       # 84.0
print(scores.max())        # 92
print(scores.shape)        # (4,)

Try It

Create a Series called grades with the following student scores: Alice: 87, Bob: 92, Carol: 78, David: 95. Print the Series, then calculate and print the mean score. Finally, create a boolean Series showing which students scored above 85.

import pandas as pd

grades = pd.Series({"Alice": 87, "Bob": 92, "Carol": 78, "David": 95})
print(grades)
print(f"Mean: {grades.mean()}")
print(grades > 85)

Key Takeaways

• A Series is a one-dimensional labeled array, the foundation of pandas
• The index provides labels for accessing and slicing data
• Vectorized operations let you transform entire columns without loops
• Dictionaries are a natural source for Series with meaningful labels

Practice Challenge

You have a dictionary representing monthly rainfall in millimeters: {"Jan": 45, "Feb": 38, "Mar": 52, "Apr": 61, "May": 48, "Jun": 35}. Create a Series from it, then calculate the total rainfall and the average monthly rainfall. Which month had the most rain? Which had the least?