熊猫Sqlite和重采样错误仅对DatetimeIndex有效

时间:2020-10-09 15:24:50

标签: python pandas sqlite

我正在尝试使用熊猫和sqlite将数据读入数据框。

如果我从CSV文件中读取代码,我认为此代码可以重新采样到每小时平均值,但是我不确定为什么从Sqlite中读取代码吗?抱歉,我对db知之甚少,非常感谢任何提示。.

如果我运行以下代码,则可以打印第一个df,但会重新采样错误:

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)

输出:

>>> 
=== 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'
>>> 

编辑

这似乎可以将日期时间索引从index转换为DatetimeIndex

df.index=pd.to_datetime(df.index)

See this other SO POST.

1 个答案:

答案 0 :(得分:0)

您需要使用Datetimeindex,而忘记了inplace=True

尝试一下:

df.set_index('Date', inplace=True)

代替此:

df.set_index('Date')

这应该解决它。

您可以获得有关 Datatimeindex here

的更多信息