I have weekly data from Yahoo Finance
Open High Low Close Adj Close Volume
Date
1999-12-27 0.901228 0.918527 0.888393 0.917969 0.782493 1.638112e+08
2000-01-03 0.936384 1.004464 0.848214 0.888393 0.757282 3.055203e+09
2000-01-10 0.910714 0.912946 0.772321 0.896763 0.764417 3.345742e+09
2000-01-17 0.901786 1.084821 0.896763 0.993862 0.847186 3.383878e+09
2000-01-24 0.968192 1.019531 0.898438 0.907366 0.773455 2.068674e+09
2000-01-31 0.901786 0.982143 0.843750 0.964286 0.821975 2.384424e+09
2000-02-07 0.964286 1.045759 0.945871 0.970982 0.827682 1.664309e+09
2000-02-14 0.976004 1.070871 0.969866 0.993304 0.846710 1.754469e+09
2000-02-21 0.983259 1.063616 0.952567 0.985491 0.840050 1.520971e+09
2000-02-28 0.983259 1.179129 0.967634 1.142857 0.974192 2.408918e+09
2000-03-06 1.125000 1.152902 1.055804 1.122768 0.957068 1.280126e+09
2000-03-13 1.090402 1.129464 1.017857 1.116071 0.951359 1.859290e+09
2000-03-20 1.102679 1.342634 1.085938 1.238281 1.055533 2.306293e+09
2000-03-27 1.228795 1.292411 1.119978 1.212612 1.033652 1.541019e+09
2000-04-03 1.209821 1.245536 1.042411 1.176339 1.002732 1.948621e+09
2000-04-10 1.175781 1.185268 0.936384 0.998884 0.851467 2.892669e+09
2000-04-17 0.977679 1.162946 0.973772 1.061384 0.904743 2.042757e+09
2000-04-24 1.026786 1.149554 1.024554 1.107701 0.944224 1.778358e+09
2000-05-01 1.114955 1.127232 0.987165 1.010045 0.860980 1.636018e+09
We need to resample it to biweekly, i.e. once in 2 weeks.
yahoo finance only provided the data for these intervals :
[1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo]
need something between 1 week and 1 Month i.e. 2 weeks.
Please let me know how to resample
>Solution :
I would just resample to 2-week increments and calculate each value. The opening price is the first, the high is the maximum, the low is the minimum, the close is the last, the adjusted close is also the last, and the volume is the total. See https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.resample.html
df['Date'] = pd.to_datetime(df['Date'])
df.set_index('Date', inplace=True)
d_ohlcv = {'Open': 'first',
'High': 'max',
'Low': 'min',
'Close': 'last',
'Adj Close': 'last',
'Volume': 'sum'}
df.resample('2W').agg(d_ohlcv).head(8)
Open High Low Close Adj Close Volume
Date
2000-01-02 0.901228 0.918527 0.888393 0.917969 0.782493 1.638112e+08
2000-01-16 0.936384 1.004464 0.772321 0.896763 0.764417 6.400945e+09
2000-01-30 0.901786 1.084821 0.896763 0.907366 0.773455 5.452552e+09
2000-02-13 0.901786 1.045759 0.843750 0.970982 0.827682 4.048733e+09
2000-02-27 0.976004 1.070871 0.952567 0.985491 0.840050 3.275440e+09
2000-03-12 0.983259 1.179129 0.967634 1.122768 0.957068 3.689044e+09
2000-03-26 1.090402 1.342634 1.017857 1.238281 1.055533 4.165583e+09
2000-04-09 1.228795 1.292411 1.042411 1.176339 1.002732 3.489640e+09