SML2&3

# Import neccessary libaries
import pandas as pd
from sklearn import tree
from sklearn.preprocessing import LabelEncoder
from sklearn.tree import DecisionTreeClassifier
from io import StringIO
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file_path="tennisdata.csv"

data = pd.read_csv(file_path)

print(data.head())
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# Obtain Train data and Train output
X = data.iloc[:,:-1]
print("\nThe first 5 values of Train data is \n",X.head())
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y = data.iloc[:,-1]
print("\nThe first 5 values of Train output is \n",y.head())
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# Convert then in numbers
le_outlook = LabelEncoder()
X.Outlook = le_outlook.fit_transform(X.Outlook)

le_Temperature = LabelEncoder()
X.Temperature = le_Temperature.fit_transform(X.Temperature)

le_Humidity = LabelEncoder()
X.Humidity = le_Humidity.fit_transform(X.Humidity)

le_Windy = LabelEncoder()
X.Windy = le_Windy.fit_transform(X.Windy)

print("\nNow the Train data is :\n",X.head())
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le_PlayTennis = LabelEncoder()
y = le_PlayTennis.fit_transform(y)
print("\nNow the Train output is\n",y)
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