我希望在我的 lambda 函式中包含多個列，但遇到了不應該是正確的關鍵問題。我正在尋找這一行來創建一個新列，該串列示如果任務中存在“決策”，然后將其標記為決策。否則，如果“專案”中存在“里程碑”，則將其標記為里程碑。否則，將其保留為當前任務型別。
today['New_Type'] = today[['Task','Projects','Type'].apply(lambda x,y,z: "Decision" if "Decision" in x else "Milestone" if "Milestone" in y else z)
任何想法如何調整？
uj5u.com熱心網友回復：
如果您使用常規的命名函式，這將更容易除錯。請務必在axis呼叫時指定引數apply。您撰寫的函式需要接受一個引數，該引數是三列值的元組，因此最好立即將它們解包以提高可讀性：
import pandas as pd
def task_type(row):
task, project, old_type = row
if 'decision' in task.lower():
return 'Decision'
if 'milestone' in project.lower():
return 'Milestone'
return old_type
today = pd.DataFrame({'Task': ['Make a decision.',
'Do something else.',
'Write a function.'],
'Projects': ['alpha', 'Milestone 7',
'gamma'],
'Type': ['old 1', 'old 2', 'old 3']})
today['New_Type'] = today.apply(task_type, axis=1)
today
Task Projects Type New_Type
0 Make a decision. alpha old 1 Decision
1 Do something else. Milestone 7 old 2 Milestone
2 Write a function. gamma old 3 old 3
uj5u.com熱心網友回復：
避免Series.apply（隱藏回圈）并考慮使用numpy.whereor的矢量化條件邏輯方法numpy.select：
today['New_Type'] = np.where(
today['Task'].str.contains('Decision', regex = False),
'Decision',
np.where(
today['Task'].str.contains('Milestone', regex = False),
'Milestone',
today['Task']
)
)
today['New_Type'] = np.select(
condlist = [
today['Task'].str.contains('Decision', regex = False),
today['Task'].str.contains('Milestone', regex = False)
],
choicelist = ['Decision', 'Milestone'],
default = today['Task']
)
轉載請註明出處，本文鏈接：https://www.uj5u.com/ruanti/383795.html