I'd like to get a time series with a fixed set of dates in the index. I thought that resample with freq and epoch='origin' will do the trick. It seems that I'm using this method in a wrong way. Here's an example that shows that epoch='origin' does not seem to work.
import pandas as pd
dates = pd.date_range('2022-01-01', '2022-02-01', freq="1D")
freq = '2W-MON'
vals = range(len(dates))
print(
pd.Series(vals,index = dates)
.resample(freq,
origin="epoch",
convention='end')
.sum()
.to_markdown()
)
| 0 | |
|---|---|
| 2022-01-03 00:00:00 | 3 |
| 2022-01-17 00:00:00 | 133 |
| 2022-01-31 00:00:00 | 329 |
| 2022-02-14 00:00:00 | 31 |
If I change the first date in the series to anything after the "2022-01-03", I get a different result.
dates = pd.date_range('2022-01-04', '2022-02-01', freq="1D")
freq = '2W-MON'
vals = range(len(dates))
print(
pd.Series(vals,index = dates)
.resample(freq,
origin="epoch",
convention='end')
.sum()
.to_markdown()
)
| 0 | |
|---|---|
| 2022-01-10 00:00:00 | 21 |
| 2022-01-24 00:00:00 | 189 |
| 2022-02-07 00:00:00 | 196 |
I'd expect that if the freq='2W-MON' and epoch='origin', both the examples will end up with the same dates (so, both should have either 2022-01-10 or 2022-01-03).
Is there an elegant way of forcing pandas to actually use epoch="origin"?
