[python] visualization pandas

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

In [37]:

#불러오기
df = pd.read_csv(f'/Users/grace/Desktop/Alex/Ice Cream Ratings.csv')
df

Out[37]:

DateFlavor RatingTexture RatingOverall Rating0123456

1/1/2022	0.223090	0.040220	0.600129
1/2/2022	0.635886	0.938476	0.106264
1/3/2022	0.442323	0.044154	0.598112
1/4/2022	0.389128	0.549676	0.489353
1/5/2022	0.386887	0.519439	0.988280
1/6/2022	0.877984	0.193588	0.832827
1/7/2022	0.140995	0.325110	0.105147

In [38]:

- 아래 그래프의 스타일을 정할 수 있음 

#plt 스타일 중 classic 사용
print(plt.style.available)
plt.style.use('classic')

['Solarize_Light2', '_classic_test_patch', '_mpl-gallery', '_mpl-gallery-nogrid', 'bmh', 'classic', 'dark_background', 'fast', 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn', 'seaborn-bright', 'seaborn-colorblind', 'seaborn-dark', 'seaborn-dark-palette', 'seaborn-darkgrid', 'seaborn-deep', 'seaborn-muted', 'seaborn-notebook', 'seaborn-paper', 'seaborn-pastel', 'seaborn-poster', 'seaborn-talk', 'seaborn-ticks', 'seaborn-white', 'seaborn-whitegrid', 'tableau-colorblind10']

In [39]:

- bar chart

#plt 시작, kind/title/xlabel/ylabel 추가
df.plot(kind = 'line', xlabel = 'Daily Ratings', ylabel = 'Scores',title = 'Ice Cream Ratings')

Out[39]:

<AxesSubplot:title={'center':'Ice Cream Ratings'}, xlabel='Daily Ratings', ylabel='Scores'>

In [40]:

- Making stacked bar chart, specifying the column도 가능 

       df['컬럼 명'].plot.barh(stacked=True)

#barh , stacked 추가 
df.plot.barh(stacked=True)

Out[40]:

<AxesSubplot:>

In [41]:

 

 

- scatter 는 꼭 x, y를 지정해줘야 함, s = size

#scatter tkdyd, x,y,color= yellow, size=500 설정
#scatter는 xlabel 이 아니라 x 로 써서 레이블링함
df.plot.scatter(x = 'Texture Rating', y = 'Overall Rating', s= 500,c= 'yellow')

Out[41]:

<AxesSubplot:xlabel='Texture Rating', ylabel='Overall Rating'>

In [42]:

- Histogram 만들기, bins = 아래 틱마크 명시

#histogram 만들기
df.plot.hist(bins=10)

Out[42]:

<AxesSubplot:ylabel='Frequency'>

In [43]:

- low minimum, 25%, 50%, 75%, high maximum

#boxplot 사용
df.boxplot()

Out[43]:

<AxesSubplot:>

 

In [44]:

- figsize 

#area 사용 , figsize = (10,5)
df.plot.area(figsize = (10,5))

Out[44]:

<AxesSubplot:>

In [46]:

#pie 사용, y 레이블 및 figsize=(10,10)사용 
#df.plot.pie(y = 'Flavor Rating', figsize =(10,10))
df.plot.pie(y='Flavor Rating',figsize=(10,10))

Out[46]:

<AxesSubplot:ylabel='Flavor Rating'>