Introdução à Visualização de Dados com o Seaborn
Erin Case
Data Scientist
Gráfico de linhas: nível médio de dióxido de nitrogênio ao longo do tempo
Gráfico de pontos: conta média em restaurantes, fumantes x não fumantes
Ambos mostram:
Diferenças:
Ambos mostram:
import matplotlib.pyplot as plt
import seaborn as sns
sns.catplot(x="age",
y="masculinity_important",
data=masculinity_data,
hue="feel_masculine",
kind="point")
plt.show()
import matplotlib.pyplot as plt import seaborn as sns sns.catplot(x="age", y="masculinity_important", data=masculinity_data, hue="feel_masculine", kind="point", join=False)
plt.show()
import matplotlib.pyplot as plt
import seaborn as sns
sns.catplot(x="smoker",
y="total_bill",
data=tips,
kind="point")
plt.show()
import matplotlib.pyplot as plt
import seaborn as sns
from numpy import median
sns.catplot(x="smoker",
y="total_bill",
data=tips,
kind="point",
estimator=median)
plt.show()
import matplotlib.pyplot as plt import seaborn as sns sns.catplot(x="smoker", y="total_bill", data=tips, kind="point", capsize=0.2)
plt.show()
import matplotlib.pyplot as plt import seaborn as sns sns.catplot(x="smoker", y="total_bill", data=tips, kind="point", ci=None)
plt.show()
Introdução à Visualização de Dados com o Seaborn