python - 如何使用 .loc 在 for 循环中将数据帧行追加到另一个数据帧行？

Question

假设我有以下数据框:

df_t1 = pd.DataFrame([["AAA", 1 ,2],["BBB", 0, 3],["CCC", 1, 2],["DDD", 0, 0],["EEE", 0, 3]], columns=list('ABC'))

    A   B   C
0   AAA 1   2
1   BBB 0   3
2   CCC 1   2
3   DDD 0   0
4   EEE 0   3

和

df_t2 = pd.DataFrame([["XXX", 4, 1],["YYY", 5 ,6],["ZZZ", 0, 3]], columns=list('ABC'))

    A   B   C
0   XXX 4   1
1   YYY 5   6
2   ZZZ 0   3

我可以使用下面的代码找到 df_t1 中满足特定条件的行:

df_t1.loc[(df_t1['B'] <= 2) & (df_t1['C'] > 2)]

A   B   C
1   BBB 0   3
4   EEE 0   3

df_t1.loc[(df_t1['B'] <= 3) & (df_t1['C'] > 3)]

    A   B   C
[Empty Dataframe]

我可以创建一个返回相同结果的 for 循环:

for i in value_check:
    print(df_t1.loc[(df_t1['B'] <= i) & (df_t1['C'] > i)])

A  B  C
1  BBB  0  3
4  EEE  0  3
Empty DataFrame
Columns: [A, B, C]
Index: []

但是当我尝试使用该代码将这些值附加到 df_t2 时:

value_check = [2,3]

for i in value_check:
    df_t2.append(df_t1.loc[(df_t1['B'] <= i) & (df_t1['C'] > i)])

df_t2 不变

Answer 1

使用pd.concat

df_t1 = pd.DataFrame([["AAA", 1 ,2],["BBB", 0, 3],["CCC", 1, 2],["DDD", 0, 0],["EEE", 0, 3]], columns=list('ABC'))

df_t2 = pd.DataFrame([["XXX", 4, 1],["YYY", 5 ,6],["ZZZ", 0, 3]], columns=list('ABC'))

value_check = [2, 3]

for i in value_check:
    condition = (df_t1['B'] <= i) & (df_t1['C'] > i)
    row_to_add = df_t1.loc[condition]

    df_t2 = pd.concat([df_t2, row_to_add], axis=0)