pandas Sqlite 和重采样错误仅对 DatetimeIndex 有效

Question

I am experimenting with pandas and sqlite to read data into a dataframe.

I think this code to resample to hourly averages worked if I were reading from a CSV file, but I am not sure why from Sqlite? Sorry I know very little about db any tips greatly appreciated..

If I run the code below I can print the first df but the resample errors:

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)

Output:

>>> 
=== 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'
>>> 

EDIT

This appeared to work converting the datetime index from index to DatetimeIndex

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

See this other SO POST.

Answer 1

You need to use a Datetimeindex and your forgot the inplace=True

try this:

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

instead of this:

df.set_index('Date')

this should solve it.

You can get more information about Datatimeindex here