Fetching custom time ranges¶
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import refinitiv.data as rd
rd.open_session()
/home/runner/.local/share/virtualenvs/refinitiv-data-python-cookbook-I-HIyNf4/lib/python3.10/site-packages/refinitiv/data/_access_layer/session.py:71:FutureWarning:
You open a platform session using the default value of the signon_control parameter (signon_control=True).
In future library version v2.0, this default will be changed to False.
If you want to keep the same behavior as today, you will need to set the signon_control parameter to True either in the library configuration file
({'sessions':{'platform':{'your_session_name':{'signon_control':true}}}}) or in your code where you create the Platform Session.
These alternative options are already supported in the current version of the library.
<refinitiv.data.session.Definition object at 0x7fd3747d4fd0 {name='rdp'}>
You can use the Refinitiv Data Library for Python to retrieve the stock prices for custom time ranges by passing a start and end date to the get_history function.
The inputs should be datetime.timedelta objects. The start argument is how many days before today to start the range, and the end argument is how many days before today to end the range.
This example retrieves the closing price for the Thomson Reuters stock for the last 365 calendar days:
from datetime import timedelta
rd.get_history(
"TRI.TO",
# Note that this number is negative because it's in the past
start=timedelta(days=-365),
# `end` is set to zero to draw the latest numbers
end=timedelta(days=0),
)
/home/runner/.local/share/virtualenvs/refinitiv-data-python-cookbook-I-HIyNf4/lib/python3.10/site-packages/refinitiv/data/_tools/_dataframe.py:177:FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`
| TRI.TO | TRDPRC_1 | HIGH_1 | LOW_1 | ACVOL_UNS | OPEN_PRC | BID | ASK | VWAP | BLKCOUNT | BLKVOLUM | NUM_MOVES | TRD_STATUS | SALTIM | TRNOVR_UNS | NAVALUE | ALT_CLOSE |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Date | ||||||||||||||||
| 2023-04-28 | 178.16 | 180.0 | 177.69 | 277310 | 179.12 | 177.81 | 178.58 | 178.2732 | 3 | 41200 | 1543 | 1 | 72929 | 49436947.31 | <NA> | 178.16 |
| 2023-05-01 | 179.07 | 179.57 | 177.6 | 404868 | 178.19 | 178.71 | 179.49 | 179.0182 | 6 | 274800 | 1079 | 1 | 72918 | 72478735.28 | <NA> | 179.07 |
| 2023-05-02 | 178.12 | 179.72 | 169.77 | 562216 | 173.89 | 178.0 | 178.75 | 177.1083 | <NA> | <NA> | 4539 | 1 | 72000 | 99573102.02 | <NA> | 178.12 |
| 2023-05-03 | 170.09 | 175.82 | 169.78 | 502402 | 175.27 | 169.53 | 170.78 | 171.4574 | 2 | 67000 | 3701 | 1 | 72906 | 86140538.03 | <NA> | 170.09 |
| 2023-05-04 | 161.2 | 169.3 | 160.93 | 641898 | 169.04 | 160.8 | 163.68 | 163.3714 | <NA> | <NA> | 5616 | 1 | 72000 | 104867796.36 | <NA> | 161.2 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 2024-04-19 | 206.67 | 208.5 | 205.69 | 204696 | 207.67 | 206.19 | 206.68 | 206.82967 | <NA> | <NA> | 1606 | 1 | 72000 | 42337205.6 | <NA> | 206.67 |
| 2024-04-22 | 209.58 | 210.86 | 206.96 | 179357 | 206.96 | 209.22 | 210.12 | 209.52944 | <NA> | <NA> | 1505 | 1 | 72000 | 37580571.24 | <NA> | 209.58 |
| 2024-04-23 | 209.92 | 211.48 | 209.37 | 206579 | 211.08 | 209.4 | 210.52 | 210.26773 | <NA> | <NA> | 1794 | 1 | 72937 | 43436897.09 | <NA> | 209.92 |
| 2024-04-24 | 209.09 | 212.61 | 208.69 | 160582 | 210.81 | 208.51 | 209.66 | 209.72646 | <NA> | <NA> | 1202 | 1 | 72979 | 33678295.08 | <NA> | 209.09 |
| 2024-04-25 | 208.35 | 209.18 | 205.67 | 170282 | 207.44 | 208.04 | 208.94 | 207.95457 | <NA> | <NA> | 1554 | 1 | 72000 | 35410920.06 | <NA> | 208.35 |
250 rows × 16 columns
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rd.close_session()