我无法随时间获得平均值。
我有特定时间的传感器读数列表,我想获取每小时的传感器平均值。
from datetime import datetime, timedelta
import numpy
import pandas
key_id = 1234
key_label = "Sensor1"
t_0 = datetime(2010,1,2,12)
data = [
[t_0 - timedelta(seconds=120), key_id, 0],
[t_0 + timedelta(seconds=1800), key_id, 1],
[t_0 + timedelta(seconds=3600 + 300), key_id, 121],
[t_0 + timedelta(seconds=3600 + 360), key_id, 1],
[t_0 + timedelta(seconds=7200 + 1800), key_id, 2],
]
df = pandas.DataFrame(list(map(lambda r: list(r), data)), columns=["TS", "KeyId", "Value"])
df_pivot = (df
.pivot(index="TS", columns="KeyId", values="Value")
.ffill()
.rename({key_id: key_label}, axis='columns')
)
def mymean(*args, **kwargs):
expected_results = [numpy.NaN, 0.5, 3, 1.5]
d0 = args[0].index[0]
if d0 == data[0][0]:
return expected_results[0]
if d0 == data[1][0]:
return expected_results[1]
if d0 == data[2][0]:
return expected_results[2]
if d0 == data[4][0]:
return expected_results[3]
return "???"
results = (df_pivot
.resample('1H')
.agg(["min", "max", "mean", "count", mymean])
)
display(df_pivot)
display(results)
预期结果在列mymean
中。在13:00和14:00之间有两个值。这两个值的平均值为61,但传感器仅停留在121分钟,因此预期的平均值应该为3(对于惰性读取器:(1 * 59 + 121 * 1)/ 60)。
KeyId Sensor1
TS
2010-01-02 11:58:00 0
2010-01-02 12:30:00 1
2010-01-02 13:05:00 121
2010-01-02 13:06:00 1
2010-01-02 14:30:00 2
Sensor1
min max mean count mymean
TS
2010-01-02 11:00:00 0 0 0 1 NaN
2010-01-02 12:00:00 1 1 1 1 0.5
2010-01-02 13:00:00 1 121 61 2 3.0
2010-01-02 14:00:00 2 2 2 1 1.5
我可以将采样频率提高到ffill
并取平均值,但这看起来效率很低。
答案 0 :(得分:0)
我是这样做的:
ffill
赋予它们值:extra_times = pandas.date_range(t_0, periods=3, freq='1H')
pdf_reindexed = (pandas
.concat([pdf_query, pandas.DataFrame(index=extra_times)], sort=False)
.sort_index()
.ffill()
)
span
:timestamp = pdf_reindexed.index.to_series()
pdf_reindexed["span"] = (timestamp.shift(-1) - timestamp).dt.seconds
value
乘以span
:pdf_reindexed["product"] = pdf_reindexed["span"] * pdf_reindexed["Sensor1"]
pdf_time_mean = (pdf_reindexed
.resample("1H")
.agg({"product": "sum"})
)
pdf_time_mean["product"] = pdf_time_mean["product"] / 3600