sklearn-導入數據(第1講)

導入數據     2020/5/27
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1.1.sklearn中導入數據方法有:pandas.read_csv,np.loadtxt,python csv.reader
1.2.sklearn中數據多爲numpy 2D,1D,pd.Series,pd.DataFrame,list
1.3.數據類型多爲np.float64,int64

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2.實例：
import csv,pandas as pd,numpy as np

# 使用numpy導入CSV數據
filename = 'pima_data.csv'
with open(filename, 'rt') as raw_data:
    data = np.loadtxt(raw_data, delimiter=',')
    print(data.shape)

# 使用Pandas導入CSV數據
filename = 'pima_data.csv'
names = ['preg', 'plas', 'pres', 'skin', 'test', 'mass', 'pedi', 'age', 'class']
data = pd.read_csv(filename, names=names)
print(data.shape)

# 使用標準的Python類庫導入CSV數據
filename = 'pima_data.csv'
with open(filename, 'rt') as raw_data:
    readers = csv.reader(raw_data, delimiter=',')
    x = list(readers)
    data = np.array(x).astype('float')
    print(data.shape)

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