Tabelas dinâmicas
Manipulação de dados com o pandas
Maggie Matsui
Senior Content Developer at DataCamp
Do agrupamento à tabela dinâmica
dogs.groupby("color")["weight_kg"].mean()
color
Black 26
Brown 24
Gray 17
Tan 2
White 74
Name: weight_kg, dtype: int64
dogs.pivot_table(values="weight_kg",
index="color")
weight_kg
color
Black 26.5
Brown 24.0
Gray 17.0
Tan 2.0
White 74.0
Estatísticas diferentes
dogs.pivot_table(values="weight_kg", index="color", aggfunc="median")
weight_kg
color
Black 26.5
Brown 24.0
Gray 17.0
Tan 2.0
White 74.0
Várias estatísticas
dogs.pivot_table(values="weight_kg", index="color", aggfunc=["mean", "median"])
mean median
weight_kg weight_kg
color
Black 26.5 26.5
Brown 24.0 24.0
Gray 17.0 17.0
Tan 2.0 2.0
White 74.0 74.0
Tabelas dinâmicas com duas variáveis
dogs.groupby(["color", "breed"])["weight_kg"].mean()
dogs.pivot_table(values="weight_kg", index="color", columns="breed")
breed Chihuahua Chow Chow Labrador Poodle Schnauzer St. Bernard
color
Black NaN NaN 29.0 24.0 NaN NaN
Brown NaN 24.0 24.0 NaN NaN NaN
Gray NaN NaN NaN NaN 17.0 NaN
Tan 2.0 NaN NaN NaN NaN NaN
White NaN NaN NaN NaN NaN 74.0
Preenchimento de valores faltantes em tabelas dinâmicas
dogs.pivot_table(values="weight_kg", index="color", columns="breed", fill_value=0)
breed Chihuahua Chow Chow Labrador Poodle Schnauzer St. Bernard
color
Black 0 0 29 24 0 0
Brown 0 24 24 0 0 0
Gray 0 0 0 0 17 0
Tan 2 0 0 0 0 0
White 0 0 0 0 0 74
Somas com tabelas dinâmicas
dogs.pivot_table(values="weight_kg", index="color", columns="breed",
fill_value=0, margins=True)
breed Chihuahua Chow Chow Labrador Poodle Schnauzer St. Bernard All
color
Black 0 0 29 24 0 0 26.500000
Brown 0 24 24 0 0 0 24.000000
Gray 0 0 0 0 17 0 17.000000
Tan 2 0 0 0 0 0 2.000000
White 0 0 0 0 0 74 74.000000
All 2 24 26 24 17 74 27.714286
Vamos praticar!
Manipulação de dados com o pandas
