[EDA] seaborn lmplot, heatmap, pairplot

lmplot

# lmplot: total_bill과 tip 사이 관계 파악

sns.set_style('darkgrid')
sns.lmplot(x='total_bill', y='tip', data=tips, height=7)
plt.show()

• hue

# hue option

sns.set_style('darkgrid')
sns.lmplot(x='total_bill', y='tip', data=tips, height=7, hue='smoker')

seaborn 예제3: flights data

flights = sns.load_dataset('flights')

# pivot
# index, column, values
flights = flights.pivot(index='month', columns='year', values='passengers')

heatmap

# heatmap

plt.figure(figsize=(10, 8))
sns.heatmap(data=flights, annot=True, fmt='d')  # annot=True 데이터 값 표시, fmt='d' 정수형 표현
plt.show()

• colormap

# colormap

plt.figure(figsize=(10, 8))
sns.heatmap(flights, annot=True, fmt='d', cmap='YlGnBu')
plt.show()

seaborn 예제4: iris data

iris = sns.load_dataset('iris')

pairplot

• hue

# pairplot

sns.set_style('ticks')
sns.pairplot(iris, hue='species')

# 원하는 컬럼만 pairplot

sns.pairplot(iris, 
             x_vars=['sepal_width', 'sepal_length'],
             y_vars=['petal_width', 'petal_length'])
plt.show()

seaborn 예제5: anscombe data

• lmplot

anscombe = sns.load_dataset('anscombe')

• order option

sns.set_style('darkgrid')
sns.lmplot(x='x', 
           y='y', 
           data=anscombe.query("dataset == 'II'"), 
           order=2,
           ci=None, 
           height=7, 
           scatter_kws={'s': 50})  
plt.show()

• outlier

sns.set_style('darkgrid')
sns.lmplot(x='x', 
           y='y', 
           data=anscombe.query("dataset == 'III'"),
           robust=True, 
           ci=None, 
           height=7, 
           scatter_kws={'s': 50})  
plt.show()

📌 서울시 범죄현황 데이터 시각화

import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib import rc

plt.rcParams['axes.unicode_minus'] = False
get_ipython().run_line_magic('matplotlib', 'inline')
rc('font', family='Arial Unicode MS')

# '인구수', 'CCTV'와 '살인', '강도'의 상관관계 확인

def drawGraph():
    sns.pairplot(
        data=crime_anal_norm,
        x_vars=['인구수', 'CCTV'],
        y_vars=['살인', '강도'],
        kind='reg',
        height=4)
    plt.show()
drawGraph()