以下のコードは1つの例です。
import pandas as pd
import numpy as np
today = pd.datetime.today().date()
df = pd.DataFrame({"date": pd.date_range('20170901','20170930', freq='D'),
"open": np.random.rand(30),
"high": np.random.rand(30),
"low": np.random.rand(30),
"close": np.random.rand(30),
"volume": np.random.rand(30)},
columns = ["date", "open", "high", "low", "close", "volume"])
selected_date = pd.date_range(today - pd.to_timedelta(20, unit='d'), today, freq='D')
df_selected = df[df["date"].isin(selected_date)]
# Out[40]:
# date open high low close volume
# 7 2017-09-08 0.790424 0.999621 0.139619 0.669588 0.476784
# 8 2017-09-09 0.190239 0.439975 0.362905 0.018472 0.905773
# 9 2017-09-10 0.184327 0.686411 0.124636 0.741130 0.132774
# 10 2017-09-11 0.346019 0.022173 0.422704 0.159098 0.011801
# 11 2017-09-12 0.549928 0.228514 0.851650 0.824209 0.756816
# 12 2017-09-13 0.413550 0.994019 0.340958 0.905432 0.289316
# 13 2017-09-14 0.435034 0.485978 0.768520 0.534148 0.276084
# 14 2017-09-15 0.839840 0.775490 0.481123 0.911378 0.928908
# 15 2017-09-16 0.442393 0.512893 0.519516 0.844619 0.813230
# 16 2017-09-17 0.723789 0.646345 0.081776 0.388496 0.391421
# 17 2017-09-18 0.964289 0.849776 0.156879 0.663885 0.062165
# 18 2017-09-19 0.001000 0.174666 0.694151 0.777330 0.739554
# 19 2017-09-20 0.426997 0.541273 0.789910 0.218263 0.748694
# 20 2017-09-21 0.217904 0.295377 0.087909 0.765242 0.555663
# 21 2017-09-22 0.910734 0.848182 0.476946 0.374580 0.079900
# 22 2017-09-23 0.160963 0.795219 0.956262 0.744048 0.645552
# 23 2017-09-24 0.412634 0.722252 0.226693 0.524794 0.910259
# 24 2017-09-25 0.535072 0.131761 0.931164 0.618055 0.542512
# 25 2017-09-26 0.697222 0.552784 0.537899 0.773403 0.916538
# 26 2017-09-27 0.257628 0.479550 0.539444 0.540076 0.344933
# 27 2017-09-28 0.270114 0.914036 0.137004 0.939907 0.736016
さらに、クローズアイテムの最大値と最小値は、次のようにして求められます。
df_max = df_selected[df_selected['close'] == df_selected['close'].max()]
# Out[48]:
# date open high low close volume
# 27 2017-09-28 0.270114 0.914036 0.137004 0.939907 0.736016
df_min = df_selected[df_selected['close'] == df_selected['close'].min()]
# Out[49]:
# date open high low close volume
# 8 2017-09-09 0.190239 0.439975 0.362905 0.018472 0.905773
あなたは私から8時間までupvoteを持っています。学ぶほどのこと。 – Dark