[英]Pandas dataframe.resample TypeError 'Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'RangeIndex'
[英]pandas Sqlite and resample error Only valid with DatetimeIndex
我正在嘗試使用 pandas 和 sqlite 將數據讀入數據幀。
如果我從 CSV 文件中讀取數據,我認為這段重新采樣到每小時平均值的代碼是有效的,但我不確定為什么從 Sqlite 中讀取數據? 抱歉,我對 db 知之甚少,非常感謝任何提示..
如果我運行下面的代碼,我可以打印第一個 df 但重采樣錯誤:
import pandas as pd
from sqlalchemy import create_engine
import sqlite3
con = sqlite3.connect('./save_data.db')
df = pd.read_sql("SELECT * from all_data", con, index_col='Date', parse_dates=True)
df.set_index('Date')
print(df)
hourly_avg['kW'] = df['kW'].resample('H').mean()
print('hourly_avg.kW', hourly_avg.kW)
輸出:
>>>
=== RESTART: C:\Users\Desktop\tester\Test.py ===
Date kW
0 2020-10-08 12:23:30.968967 68.129997
1 2020-10-08 12:25:39.375298 68.129997
2 2020-10-08 12:26:52.939991 68.129997
3 2020-10-08 12:27:57.839540 68.129997
4 2020-10-08 12:29:02.382524 68.129997
... ... ...
1917 2020-10-09 10:14:35.113254 68.149994
1918 2020-10-09 10:15:08.840759 68.189995
1919 2020-10-09 10:15:41.873328 68.249992
1920 2020-10-09 10:16:14.953312 68.289993
1921 2020-10-09 10:16:48.043465 68.289993
[1922 rows x 2 columns]
Traceback (most recent call last):
File "C:\Users\Desktop\tester\Test.py", line 11, in <module>
hourly_avg['kW'] = df['kW'].resample('H').mean()
File "C:\Users\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\generic.py", line 8087, in resample
offset=offset,
File "C:\Users\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\resample.py", line 1269, in get_resampler
return tg._get_resampler(obj, kind=kind)
File "C:\Users\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\resample.py", line 1435, in _get_resampler
"Only valid with DatetimeIndex, "
TypeError: Only valid with DatetimeIndex, TimedeltaIndex or PeriodIndex, but got an instance of 'RangeIndex'
>>>
編輯
這似乎可以將日期時間索引從index
轉換為日期DatetimeIndex
index
df.index=pd.to_datetime(df.index)
您需要使用Datetimeindex
而您忘記了inplace=True
嘗試這個:
df.set_index('Date', inplace=True)
而不是這個:
df.set_index('Date')
這應該解決它。
您可以在此處獲取有關Datatimeindex 的更多信息
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