我正在尝试将一列时间戳放入数据帧中。时间戳的格式为 0:00:00,我认为它们是字符串。我尝试使用 uber.dtypes() ,但它一直返回错误:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-4-b4120eada070> in <module>()
----> 1 uber.dtypes()
TypeError: 'Series' object is not callable
picture of dataframe for reference
uber["Time"].head().to_dict()
返回以下内容:
{0: '0:11:00', 1: '0:17:00', 2: '0:21:00', 3: '0:28:00', 4: '0:33:00'}
当我使用这些垃圾箱和标签时:
bins = np.arange(0, 25, 1)
labels = [
"0:00-1:00",
"1:01-2:00",
"2:01-3:00",
"3:01-4:00",
"4:01-5:00",
"5:01-6:00",
"6:01-7:00",
"7:01-8:00",
"8:01-9:00",
"9:01-10:00",
"10:01-11:00",
"11:01-12:00",
"12:01-13:00",
"13:01-14:00",
"14:01-15:00",
"15:01-16:00",
"16:01-17:00",
"17:01-18:00",
"18:01-19:00",
"19:01-20:00",
"20:01-21:00",
"21:01-22:00",
"22:01-23:00",
"23:01-24:00"
]
uber["Hour"] = pd.cut(uber["Time"], bins, labels = labels)
我收到以下错误:
TypeError: '<' not supported between instances of 'int' and 'str'
如果我将垃圾箱更改为:
bins = str(np.arange(0, 25, 1)
我收到此错误:
AxisError: axis -1 is out of bounds for array of dimension 0
我意识到我可能可以将这些转换为秒,然后使用 pd.to_numeric() 将列转换为整数,以便可以将它们分箱,但我已经浏览了文档,但仍然不清楚如何使用日期时间或时间(我可以做很长的方法并乘以秒和分钟)。
1) 如何使用日期时间或时间将这些时间戳转换为秒?
2)有没有办法在不将时间戳转换为秒的情况下对它们进行分类?
我还尝试将 uber["Time"] 中的值转换为 datetime.time 对象,并在分箱之前将它们插入到新列 ["Time Object"] 中:
for i in range(len(uber["Time"])):
uber.loc[i, "Time Object"] = datetime.datetime.strptime(uber.loc[i, "Time"], "%H:%M:%S").time()
如果我尝试使用 [“Time Object”] 列进行装箱:
uber["Hour"] = pd.cut(uber["Time Object"], bins = 24, labels = labels)
然后我收到此错误:
TypeError: '<=' not supported between instances of 'datetime.time' and 'str'
如果我尝试使用 [“Time Object”] 列的小时进行分箱:
uber["Hour"] = pd.cut(uber["Time Object"].hour, bins = 24, labels = labels)
我收到此错误:
AttributeError: 'Series' object has no attribute 'hour'
最佳答案
您可以尝试花几分钟时间并将其放入垃圾箱
uber = pd.DataFrame()
labels = [str(i)+':01-'+str(i+1)+':00' for i in range(59)]
uber['Time'] = {0: '0:11:00', 1: '0:17:00', 2: '0:21:00', 3: '0:28:00', 4: '0:33:00'}.values()
uber.Time = pd.to_timedelta(uber.Time)
pd.cut(uber.Time.dt.seconds/60,bins,labels=labels)
输出:
0 10:01-11:00
1 16:01-17:00
2 20:01-21:00
3 27:01-28:00
4 32:01-33:00
Name: Time, dtype: category
Categories (59, object): [0:01-1:00 < 1:01-2:00 < 2:01-3:00 < 3:01-4:00 ... 55:01-56:00 < 56:01-57:00 < 57:01-58:00 < 58:01-59:00]
关于python - 对 Pandas 时间戳列进行分箱,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/53699809/