Apprendre Understanding Series | Pandas Foundations

AI in Action


              12345678
            
import pandas as pd  

scores = pd.Series([88, 92, 79, 93], index=["Alice", "Bob", "Carol", "Dan"], name="Exam Scores")  

print(scores)
print(scores.index)
print(scores.dtype)
print(scores.size)

Definition

A Series is the simplest pandas data structure: a one-dimensional labeled array. You can think of it as a single column of a table, with values and an index that labels them.

Creating Series

You can create a Series from common Python data structures, such as dictionaries and lists.

From a Dictionary


              1234
            
import pandas as pd

scores = pd.Series({"Alice": 88, "Bob": 92, "Carol": 79, "Dan": 93})  
print(scores)

Here, dictionary keys become the index labels.

From a List


              1234
            
import pandas as pd

grades = pd.Series([88, 92, 79, 93])  
print(grades)

Pandas automatically generates an index (0, 1, 2, 3).

Metadata

A Series also carries information about itself:


              12345678
            
import pandas as pd

grades = pd.Series([88, 92, 79, 93], name="Exam Scores")  

print(grades.index)
print(grades.dtype)
print(grades.name)
print(grades.size)

.index: index labels;
.dtype: data type of values;
.name: name of the Series;
.size: number of elements.

1. What are the two main components of a pandas Series?

2. Which attribute shows the data type of a Series?

Tout était clair ?

Merci pour vos commentaires !

Section 1. Chapitre 2

Demandez à l'IA

Posez n'importe quelle question ou essayez l'une des questions suggérées pour commencer notre discussion

Glissez pour afficher le menu