Comments (5)
I don't want to be disrespectful, but this part
!wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz !tar xvzf ta-lib-0.4.0-src.tar.gz import os os.chdir('ta-lib') !./configure --prefix=/usr !make !make install
Looks very unclean and clumsy :/ Why we don't use conda here 🤔 like so
!conda install -y -c conda-forge ta-lib
?
@emarashliev
Thanks for your suggestion.
Indeed these are not neat enough, but we have to consider about the case that there are users running the notebooks on online editors like Google Colab. Using conda could only be more inconvenient in this situation. But if there's a better way with elegant codes that work for both users on Colab and local/conda environment, feel free to make adjustment and submit a PR!
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I have the same issue
from finrl-tutorials.
Hi! You may generate those data by following the demo notebook here. The demo notebook is an example of getting data from Tushare, you may also try other data sources or even make your own data. Just to make share you have tic
, time
, and close
in your columns.
from finrl-tutorials.
I don't want to be disrespectful, but this part
!wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
!tar xvzf ta-lib-0.4.0-src.tar.gz
import os
os.chdir('ta-lib')
!./configure --prefix=/usr
!make
!make install
Looks very unclean and clumsy :/
Why we don't use conda here 🤔 like so !conda install -y -c conda-forge ta-lib
?
from finrl-tutorials.
where do I find the data file (train_data.csv, trade_data.csv )for those notebooks
@scotthuang1989
The files as well as the refined notebooks of Stock NeurIPS2018 were added in the directory
./1-Introduction/Stock_NeurIPS2018
You can directly use the two provided csv files, or run the notebook Stock_NeurIPS2018_1_Data.ipynb first and save the generated csv files.
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Related Issues (20)
- NeurIPS2018 no speedup with increasing batch size HOT 2
- Please help confirm or correct my understanding!
- NeurIPS2018 train test not matching HOT 4
- future leakage? HOT 1
- How to backtest results on paper trading demo
- error in FinRL-Tutorials/3-Practical/FinRL_PaperTrading_Demo.ipynb HOT 2
- error encountered in yahoo downloader in the very first tutorial notebook HOT 1
- I can't reproduction the result of "Stock_NeurIPS2018/Stock_NeurIPS2018_3_Backtest.ipynb" HOT 1
- I meet an error when I run FinRL_PortfolioAllocation_NeurIPS_2020.ipynb in BackTestPlot,please help me!!! HOT 1
- FinRL_MultiCrypto_Trading.py no longer working due to changes in ElegantRL and FinRL-Meta HOT 1
- When I run FinRL_China_A_Share_Market.ipynb, the actions obtained from the training only traded in the firs two days. How to solve this problem? HOT 1
- ValueError: If using all scalar values, you must pass an index || Deep Reinforcement Learning for Stock Trading from Scratch: Multiple Stock Trading Using Ensemble Strategy
- AssertionError in Stock_NeurIPS2018_2_Train.ipynb
- China_A_share_market_tushare.py cannot run correctly.
- Stock_NeurIPS2018_2_Train only trains A2C
- Error/Introduction Stock NeurIPS2018 Part 3. Backtest.ipynb HOT 2
- Is it possible to continue a previously started ensemble model training?
- about the variable 'processed_full' in Stock_NeurIPS2018_SB3.py
- There is a bug in 1-Introduction Stock_NeurIPS2018_SB3.ipynb
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