嗨，我有一個資料集，其中 col 值看起來像 08:25:00 我想要作為早上的結果值。
10:36:00 - Morning
16:00:00 - afternoon
17:00:00 - afternoon
19:00:00 -evening
我嘗試了以下步驟，但對于幾行，我得到了 Nan 值和不正確的結果
df['PNR_CREATE_TM_1']=pd.DataFrame({'PNR_CREATE_TM':range(1,25)})
bns=[0,4,8,12,16,20,24]
part_days=['Late Night','Early Morning','Morning','Noon','Evening','Night']
df['PNR_CREATE_SESSION'] = pd.cut(df['PNR_CREATE_TM_1'],bins=bns,labels=part_days,include_lowest=True)
uj5u.com熱心網友回復：
假設“時間”作為字串型別的初始列，您可以拆分小時，并使用pandas.cut：
df = pd.DataFrame({'time': ['10:36:00', '16:00:00', '17:00:00', '19:00:00']})
bns=[0,4,8,12,16,20,24]
part_days=['Late Night','Early Morning','Morning','Noon','Evening','Night']
s = df['time'].str.split(':').str[0].astype(int)
df['part'] = pd.cut(s, bins=bns, labels=part_days, include_lowest=True)
輸出：
time part
0 10:36:00 Morning
1 16:00:00 Noon
2 17:00:00 Evening
3 19:00:00 Evening
uj5u.com熱心網友回復：
將值轉換為日期to_datetime時間并獲取小時數Series.dt.hour：
df['PNR_CREATE_SESSION'] = pd.cut(pd.to_datetime(df['PNR_CREATE_TM_1']).dt.hour,
bins=bns,
labels=part_days,
include_lowest=True)
或者如果 python 物件時間：
df['PNR_CREATE_SESSION'] = pd.cut(pd.to_datetime(df['PNR_CREATE_TM_1'].astype(str)).dt.hour,
bins=bns,
labels=part_days,
include_lowest=True)
轉載請註明出處，本文鏈接：https://www.uj5u.com/qukuanlian/369416.html