[2025/01/02]데이터 전처리 & 시각화 숙제

이제는 응용! 배운 것을 다 활용해서 숙제를 해볼까요?

 

1. flights 데이터셋을 활용해서 그래프를 그려봅시다

import seaborn as sns

import matplotlib.pyplot as plt

# Seaborn의 내장 데이터셋 'flights' 불러오기

flights_data = sns.load_dataset('flights')

1) 연도별 총 승객 수

yearly_passengers = flights_data[['year','passengers']].groupby('year').sum().reset_index()

plt.bar(yearly_passengers['year'], yearly_passengers['passengers'])

plt.xlabel('Year')

plt.ylabel('Passengers')

plt.title('Total Passengers')

plt.show()

#

 

2) 연도별 평균 승객 수

yearly_passengers = flights_data[['year','passengers']].groupby('year').mean()

plt.plot(yearly_passengers.index, yearly_passengers.values, color='gray', marker = 'o', linestyle = '--')

plt.xlabel('Year')

plt.ylabel('Passengers')

plt.title('Average Passengers')

plt.show()

#

 

3) 승객 수 분포

plt.hist(flights_data['passengers'], bins=30, color = "orange", edgecolor = 'white')

plt.xlabel('Passengers')

plt.ylabel('Frequency')

plt.title('Passengers Distribution')

plt.show()

#

 

4) 연도별 승객 수와 월간 승객 수   ----  이해 못함 나중에 다시 풀어보기

for month in flights_data['month'].unique():

    plt.scatter(flights_data[flights_data['month'] == month]['year'],

                flights_data[flights_data['month'] == month]['passengers'],

                label=month)

plt.title('Passengers per Year by Month')

plt.xlabel('Year')

plt.ylabel('Passengers')

plt.legend()

plt.show()

#

 

5) 월별 승객 수 분포

monthly_passengers = flights_data[['month','passengers']].groupby('month').sum().reset_index()

plt.bar(monthly_passengers['month'], monthly_passengers['passengers'], color = 'skyblue')

plt.xlabel('Month')

plt.ylabel('Passengers')

plt.title('Monthly Passengers')

plt.show()

#

 

5번 정답  ---- boxplot 아직 잘 모르겠음

plt.figure(figsize=(8, 6))

plt.boxplot([flights_data[flights_data['month'] == month]['passengers'] for month in flights_data['month'].unique()],

            labels=flights_data['month'].unique())

plt.title('Passengers Distribution by Month')

plt.xlabel('Month')

plt.ylabel('Passengers')

plt.show()

#

2. tips 데이터셋을 활용해서 그래프를 그려봅시다

import seaborn as sns

import matplotlib.pyplot as plt

# Seaborn의 내장 데이터셋 'tips' 불러오기

tips_data = sns.load_dataset('tips')

1) 요일별 팁 금액의 평균

 제목 : Average Tips by Day

 X축 : Day of the Week

 Y축 : Average Tip Amount

 

avg_tip = tips_data[['day','tip']].groupby('day').mean()

plt.plot(avg_tip.index, avg_tip.values, marker = 'o', color = 'tomato', linestyle = '--')

plt.xlabel('Day of the Week')

plt.ylabel('Average Tip Amount')

plt.title('Average Tips by Day')

plt.show()

#

 

2) 요일별 총 팁 금액

 제목 : Total Tips by Day

 X축 : Day of the Week

 Y축 : Total Tip Amount

 

avg_tip = tips_data[['day','tip']].groupby('day').sum().reset_index()

plt.bar(avg_tip['day'], avg_tip['tip'], color = 'limegreen')

plt.xlabel('Day of the Week')

plt.ylabel('Total Tip Amount')

plt.title('Total Tips by Day')

plt.show()

#

 

3) 식사 금액 분포

 제목 : Distribution of Total Bill

 X축 : Total Bill Amount

 Y축 : Frequency

 

plt.hist(tips_data['total_bill'], bins = 50, color = 'darkcyan', edgecolor = 'thistle')

plt.xlabel('Total Bill Amount')

plt.ylabel('Frequency')

plt.title('Distribution of Total Bill')

plt.show()

#

 

4) 식사 금액과 팁 금액의 관계

 제목 : Tip Amount vs Total Bill

 X축 : Total Bill Amount

 Y축 : Tip Amount

 

plt.scatter(tips_data['total_bill'], tips_data['tip'], color = 'gold', edgecolors= 'black')

plt.xlabel('Total Bill Amount')

plt.ylabel('Tip Amount')

plt.title('Tip Amount vs Total Bill')

plt.show()

#

 

5) 요일별 식사 금액 분포

 제목 : Total Bill Distribution by Day

 X축 : Day of the Week

 Y축 : Total Bill Amount

 

plt.boxplot([tips_data[tips_data['day'] == day]['total_bill']\

              for day in tips_data['day'].unique()]\

                , labels = tips_data['day'].unique())

plt.xlabel('Day of the Week')

plt.ylabel('Total Bill Amount')

plt.title('Total Bill Distribution by Day')

plt.show()

#