import pandas as pd
data = pd.read_csv('consumption_data.csv', encoding = 'big5')
data.head(6)
地區 | 廣告 | 消費金額 | |
---|---|---|---|
0 | 南部 | 廣告1 | 20.83 |
1 | 南部 | 廣告1 | 21.45 |
2 | 中部 | 廣告1 | 27.09 |
3 | 南部 | 廣告1 | 14.09 |
4 | 南部 | 廣告1 | 31.23 |
5 | 南部 | 廣告1 | 27.20 |
data.isnull().any()
地區 False 廣告 False 消費金額 False dtype: bool
alist = data[data ['廣告'] == '廣告1']['消費金額'].tolist()
blist = data[data ['廣告'] == '廣告2']['消費金額'].tolist()
clist = data[data ['廣告'] == '廣告3']['消費金額'].tolist()
alist
[20.83, 21.45, 27.09, 14.09, 31.23, 27.2, 26.65, 22.22, 21.68, 22.62, 12.89, 17.17, 15.86, 14.41, 14.88, 10.62, 16.81, 11.52, 15.84, 16.7, 18.3, 24.57, 21.74, 20.56, 17.35, 17.04, 20.2, 19.73, 24.23, 14.14, 18.52, 18.64, 15.61, 21.62, 13.22, 14.16, 14.65, 19.71, 17.84, 19.53, 15.18, 20.44, 26.66, 20.3, 29.63, 23.87, 14.36, 20.99, 15.19, 21.39, 21.43, 17.81, 9.36, 29.45, 12.69, 14.32, 9.79, 22.08, 14.63, 11.68, 7.98, 8.05, 8.19, 18.14, 28.34, 6.08, 13.13, 11.71, 17.69, 17.72, 7.44, 18.07, 26.62, 6.9, 11.44, 26.96, 17.9, 10.84, 15.88, 10.17, 14.99, 16.0, 18.35, 6.54, 6.92, 14.6, 24.66, 17.4, 17.72, 11.9, 16.81, 23.21, 18.96, 19.38, 3.58, 19.35, 12.63, 4.72, 12.43, 28.97, 12.52, 25.36, 8.41, 25.26, 17.77, 18.23, 8.97, 11.89, 14.03, 15.5, 17.62, 15.43, 16.82, 20.7, 15.34, 19.84, 13.75, 19.0, 22.23, 14.81]
blist
[20.23, 18.1, 12.34, 24.08, 22.39, 19.79, 19.39, 18.76, 21.6, 23.54, 24.05, 13.31, 12.49, 12.18, 18.48, 18.13, 25.57, 25.15, 20.68, 19.87, 8.12, 12.04, 24.12, 30.84, 19.44, 14.37, 18.41, 16.16, 19.16, 11.99, 9.6, 9.62, 9.78, 11.59, 15.38, 18.89, 23.48, 8.75, 15.68, 11.08, 21.45, 2.18, 19.48, 23.4, 23.25, 19.85, 14.53, 11.33, 21.77, 30.69, 11.83, 17.08, 21.87, 15.16, 20.76, 13.36, 8.6, 15.22, 14.64, 20.54, 8.57, 18.5, 15.38, 11.76, 14.06, 13.54, 15.4, 31.68, 12.96, 18.21, 20.41, 14.14, 19.03, 7.36, 15.82, 16.01, 16.5, 17.58, 11.65, 16.92, 12.02, 14.72, 25.81, 9.75, 17.82, 20.22, 22.86, 11.81, 13.37, 10.89, 11.19, 23.6, 15.37, 18.56, 4.78, 16.24, 7.1, 19.19, 15.26, 6.31, 1.22, 9.91, 15.09, 17.39, 14.64, 4.93, 13.02, 6.67, 10.93, 12.36, 21.06, 7.37, 3.33, 7.12, 5.86, 19.69, 10.94, 8.59, 17.0, 6.0]
clist
[8.81, 20.26, 17.46, 25.48, 22.64, 19.99, 19.45, 16.43, 20.63, 14.76, 26.08, 22.07, 25.07, 17.85, 21.66, 18.34, 22.84, 20.89, 18.98, 14.12, 23.17, 18.7, 13.97, 22.62, 18.88, 23.74, 14.61, 21.63, 19.18, 20.3, 15.89, 27.04, 12.75, 23.96, 15.73, 23.71, 14.96, 20.35, 14.79, 7.54, 13.37, 12.49, 3.3, 7.63, 18.38, 1.65, 18.49, 15.91, 14.21, 17.5, 6.04, 9.76, 18.25, 16.33, 4.29, 11.45, 17.09, 5.66, 12.74, 20.28, 14.29, 10.49, 9.48, 11.15, 15.07, 21.88, 0.63, 19.52, 6.24, 16.86, 12.88, 21.33, 10.11, 17.47, 21.28, 19.56, 6.46, 17.44, 16.17, 21.24, 3.9, 22.93, 11.59, 28.84, 7.41, 10.38, 5.84, 6.82, 17.18, 16.29, 16.31, 23.54, 7.7, 12.74, 18.62, 9.71, 25.57, 15.13, 11.07, 13.01, 8.36, 3.76, 23.88, 16.13, 9.6, 19.43, 17.62, 19.08, 25.37, 7.96, 15.56, 12.81, 22.82, 16.87, 17.04, 9.69, 10.29, 25.52, 19.26, 2.45]