Python如何比较数据框列和2D列表（） _dataframe

我有一个数据框数据：

Stretch SB NB ... WB

那里的行有Nan。我有二维列表：

[['SB', someFloatvalue, someFloatvalue], ['SB', someFloatvalue, someFloatvalue], ['NB', someFloatvalue, someFloatvalue]][['NB', someFloatvalue, someFloatvalue], ['SB', someFloatvalue, someFloatvalue], ['NB', someFloatvalue, someFloatvalue]]

上面的每个2D列表都与Stretch中的每一行相关。我想删除所有与Strecth值不同的列表。最后, 预期结果是：

[['SB', someFloatvalue, someFloatvalue], ['SB', someFloatvalue, someFloatvalue]][['NB', someFloatvalue, someFloatvalue], ['NB', someFloatvalue, someFloatvalue]]

说明：Stretch的第一行是SB。因此, 相应的2D列表仅应在其中列出SB。依此类推… 如果在拉伸中使用Nan, 则只需按原样显示列表即可。
我的想法是将Stretch转换为元组, 因为我认为该职位很重要。它没有解决..我不知道如何映射它们。
#1你可以尝试在列表理解中使用zip()：

out = [[l for l in sub_data if l[0] == key or str(key) == "nan" ] for sub_data, key in zip(data, df.Stretch)]

或通常使用以下循环：

out_1 = [] for sub_data, key in zip(data, df.Stretch): sub = [] for l in sub_data: if l[0] == key or str(key) == "nan": sub.append(l) if len(sub) > 0: out_1.append(sub)

【Python如何比较数据框列和2D列表（）】完整代码

df = pd.DataFrame({"Stretch": ["SB", "NB", np.NaN]})data = http://www.srcmini.com/[[['SB', 123456, 123456], ['SB', 123456, 123456], ['NB', 123456, 123456]], [['NB', 123456, 123456], ['SB', 123456, 123456], ['NB', 123456, 123456]], [['NB', 123456, 123456], ['SB', 123456, 123456], ['NB', 123456, 123456]]]# Usual for loop out_1 = [[l for l in sub_data if l[0] == key or str(key) == "nan"] for sub_data, key in zip(data, df.Stretch)] print(out_1) # [[['SB', 123456, 123456], ['SB', 123456, 123456]], #[['NB', 123456, 123456], ['NB', 123456, 123456]], #[['NB', 123456, 123456], ['SB', 123456, 123456], ['NB', 123456, 123456]]]out_2 = [] for sub_data, key in zip(data, df.Stretch): sub = [] for l in sub_data: if l[0] == key or str(key) == "nan": sub.append(l) if len(sub) > 0: out_2.append(sub)print(out_2) # [[['SB', 123456, 123456], ['SB', 123456, 123456]], #[['NB', 123456, 123456], ['NB', 123456, 123456]], #[['NB', 123456, 123456], ['SB', 123456, 123456], ['NB', 123456, 123456]]]print(out_1 == out_2) # True