seaborn Published by onesixx 21-07-09 21-07-09
relation plots : 두 변수의 관계를 나타냄
categorical plots : 범주형 데이터를 대상으로 함
distribution plots : 변수들의 분포를 나타냄
regression plots : 회귀분석 결과를 나타내줌
matrix plots : 변수 간의 관계 정도를 매트릭스로 만들고 색을 입혀 나타냄
import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns sns.set_context( 'paper' ) # notebook, paper, poster : font line marker 요소 배율 설정 sns.set_palette(sns.color_palette( "colorblind" )) # Set1, color_palette() 등 sns.set_style( "whitegrid" ) tips = sns.load_dataset( "tips" ) for col in tips.columns: if pd.api.types.is_numeric_dtype(tips[col]): tips[col] = pd.to_numeric(tips[col], errors = 'coerce' ) # NaN으로 변환 raise/ignore/coerce fig, ax = plt.subplots( figsize = ( 12 , 8 )) ax.hist(tips[col], bins = 20 , color = 'skyblue' , edgecolor = 'black' ) ax.set( xlabel = col, ylabel = 'Frequency' , title = f 'Histogram of { col.capitalize() } ' ) else : #** not numeric" fig, ax = plt.subplots( figsize = ( 12 , 8 )) sns.countplot( data = tips, x = col, ax = ax) ax.set( title = f 'Count of { col.capitalize() } ' ) sns.relplot( data = tips, x = "total_bill" , y = "tip" , row = "sex" , col = "time" , #col_wrap=3, hue = "day" , palette = [ 'g' , 'y' , 'b' , "r" ], style = "smoker" , size = "size" , sizes = ( 10 , 100 ), #color="blue", kind = "scatter" , height = 5 , aspect = 1 ) flights = sns.load_dataset( "flights" ) flights_wide = flights.pivot( index = "year" , columns = "month" , values = "passengers" ) sns.relplot( data = flights, x = "year" , y = "passengers" , hue = 'month' , style = 'month' , kind = "line" ) sns.relplot( data = flights_wide, kind = "line" ) # same
