我有一個資料框，其中有一列顯示組織每個庫存專案所花費的時間（以分鐘為單位）。目標是以整數或浮點數顯示花費的分鐘數。但是，此列中的值不干凈，請參見下面的一些示例。有沒有辦法標準化并將所有內容轉換為整數或浮點數？（例如，10 小時應該是 600 分鐘）
import pandas as pd
df1 = { 'min':['420','450','480','512','560','10 hours', '10.5 hours',
'420 (all inventory)','3h ', '4.1 hours', '60**','6h', '7hours ']}
df1=pd.DataFrame(df1)
想要的輸出是這樣的
uj5u.com熱心網友回復：
我用于regex此類問題。
import regex as re
import numpy as np
import pandas as pd
df1 = { 'min':['420','450','480','512','560','10 hours', '10.5 hours',
'420 (all inventory)','3h ', '4.1 hours', '60**','6h', '7hours ']}
df1=pd.DataFrame(df1)
# Copy Dataframe for iteration
# Created a empty numpy array for parsing by index
arr = np.zeros(df1.shape[0])
df1_copy = df1.copy()
for i,j in df1_copy.iterrows():
if "h" in j["min"]:
j["min"] = re.sub(r"[a-zA-Z()\s]","",j["min"])
j["min"] = float(j["min"])
arr[i] = float(j["min"]*60)
else:
j["min"] = re.sub(r"[a-zA-Z()**\s]","",j["min"])
j["min"] = float(j["min"])
arr[i] = float(j["min"])
df1["min_clean"] = arr
print(df1)
min min_clean
0 420 420.0
1 450 450.0
2 480 480.0
3 512 512.0
4 560 560.0
5 10 hours 600.0
6 10.5 hours 630.0
7 420 (all inventory) 420.0
8 3h 180.0
9 4.1 hours 246.0
10 60** 60.0
11 6h 360.0
12 7hours 420.0
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