dataframe 删除一列或某几列

慧沁成泉

借时间和兴趣做伴

因项目需要，网上查阅了很久，看了各种回答，也没有自己操作一遍来的记忆深刻

1、删除一列

使用del函数

del df['A']

del df['B']

del df['C']

2、删除某几列

axis =1 是按列删除，=0是按行删除。

df2 = df1.drop(['vehicle_energyConsumed','vehicle_lane','vehicle_chargingStationId',
                      'vehicle_energyCharged','vehicle_energyChargedInTransit',
                      'vehicle_maximumBatteryCapacity','vehicle_id',
                      'vehicle_energyChargedStopped'],axis=1)

3、代码应用

def xgboost(path):
    df = pd.read_csv(path, sep=";") 
    df = df[df['vehicle_energyConsumed']!=0]
    df1 = df[df['vehicle_id'] == '0.110']
    y = df1['vehicle_energyConsumed'] 
    
    df2 = df1.drop(['vehicle_energyConsumed','vehicle_lane','vehicle_chargingStationId',
                      'vehicle_energyCharged','vehicle_energyChargedInTransit',
                      'vehicle_maximumBatteryCapacity','vehicle_id','vehicle_energyChargedStopped'],axis=1)
    X = df2 
   
    # XGBoost训练过程
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)
    
    params = {
        'booster': 'gbtree',
        'objective': 'reg:squarederror',
        'gamma': 0.1,
        'max_depth': 5,
        'lambda': 3,
        'subsample': 0.7,
        'colsample_bytree': 0.7,
        'min_child_weight': 3,
        'silent': 1,
        'eta': 0.1,
        'seed': 1000,
        'nthread': 4,
    }
    
    dtrain = xgb.DMatrix(X_train, y_train)
    num_rounds = 300
    plst = list(params.items())
    model = xgb.train(plst, dtrain, num_rounds)
    
    # 对测试集进行预测
    expected_y  = y_test
    dtest = xgb.DMatrix(X_test)
    predicted_y = model.predict(dtest)
    
    # 显示重要特征
    plot_importance(model)

编辑于 2021-07-19 19:55

Python

dataframe 删除一列或某几列

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