Question

我正在尝试在for循环中填充pandas个数据框列。列名是参数性的，并由循环值分配。这是我的代码：

for k in range (-1, -4, -1):
    df_orj = pd.read_csv('something.csv', sep= '\t') 

    df_train = df_orj.head(11900)   
    df_test = df_orj.tail(720) 

    SHIFT = k

    df_train.trend = df_train.trend.shift(SHIFT)
    df_train = df_train.dropna()
    df_test.trend = df_test.trend.shift(SHIFT)
    df_test = df_test.dropna()

    drop_list = some_list

    df_out = df_test[['date','price']]
    df_out.index = np.arange(0, len(df_out)) # start index from 0
    df_out["pred-1"] = np.nan
    df_out["pred-2"] = np.nan
    df_out["pred-3"] = np.nan

    df_train.drop(drop_list, 1, inplace = True )
    df_test.drop(drop_list, 1, inplace = True )

    # some processes here

    rf = RandomForestClassifier(n_estimators = 10)
    rf.fit(X_train,y_train)
    y_pred = rf.predict(X_test)
    print("accuracy score: " , rf.score(X_test, y_test))


    X_test2 = sc.transform(df_test.drop('trend', axis=1))
    y_test2 = df_test['trend'].values

    y_pred2  = rf.predict(X_test2)
    print("accuracy score: ",rf.score(X_test2, y_test2))


    name = "pred{0}".format(k)
    for i in range (0, y_test2.size):
        df_out[name][i] = y_pred2[i]

df_out.head(20)

这是我的输出：

                time_period_start  price_open  pred-1  pred-2  pred-3
697  2018-10-02T02:00:00.0000000Z       86.80     NaN     NaN     1.0
698  2018-10-02T03:00:00.0000000Z       86.65     NaN     NaN     1.0
699  2018-10-02T04:00:00.0000000Z       86.32     NaN     NaN     1.0

如您所见，仅填充pred-3。如何填充所有3个预定义列？

Answer 1

如果我的理解正确，那么您的问题是您正在获得pred-3 仅在其他两个为nan时才填充。这是因为您的df_out处于循环中，并且您正在获取最后的结果循环的迭代。您应该在循环之外定义它，以便您的信息不会丢失另外两个。

Answer 2

您在每个循环中将这3列设置为null，因此在迭代时会丢失这些值。要么将这些初始化列移至循环之前，要么可以使用以下变量进行初始化：

更改

df_out["pred-1"] = np.nan
df_out["pred-2"] = np.nan
df_out["pred-3"] = np.nan

仅在循环时初始化单个列

name = "pred{0}".format(k)
df_out[name] = np.nan

完整的代码：

for k in range (-1, -4, -1):
    df_orj = pd.read_csv('something.csv', sep= '\t') 

    df_train = df_orj.head(11900)   
    df_test = df_orj.tail(720) 

    SHIFT = k

    df_train.trend = df_train.trend.shift(SHIFT)
    df_train = df_train.dropna()
    df_test.trend = df_test.trend.shift(SHIFT)
    df_test = df_test.dropna()

    drop_list = some_list

    df_out = df_test[['date','price']]
    df_out.index = np.arange(0, len(df_out)) # start index from 0

    name = "pred{0}".format(k)
    df_out[name] = np.nan

    df_train.drop(drop_list, 1, inplace = True )
    df_test.drop(drop_list, 1, inplace = True )

    # some processes here

    rf = RandomForestClassifier(n_estimators = 10)
    rf.fit(X_train,y_train)
    y_pred = rf.predict(X_test)
    print("accuracy score: " , rf.score(X_test, y_test))


    X_test2 = sc.transform(df_test.drop('trend', axis=1))
    y_test2 = df_test['trend'].values

    y_pred2  = rf.predict(X_test2)
    print("accuracy score: ",rf.score(X_test2, y_test2))



    for i in range (0, y_test2.size):
        df_out[name][i] = y_pred2[i]

df_out.head(20)

如何在for循环中填充熊猫数据框列

2 个答案: