Metadata-Version: 2.1
Name: tse_dataloader
Version: 0.1.2
Summary: Python package for downloading Tehran Stock Exchange data and analysing
Home-page: https://github.com/aliik7/tse_dataloader
Author: Aliik7
Author-email: aliik2@gmail.com
License: UNKNOWN
Description: # tse_dataloader
        
        tse_dataloader is a python package for extracting stock historical data from Tehran Stock Exchange.
        
        [![Generic badge](https://img.shields.io/badge/pypi-v0.1.2-<COLOR>.svg)](https://shields.io/) [![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/)
        - [x] Extract data and load them in `Pandas` data frame
        - [x] Calculate SMA and EMA
        - [x] Create line charts with `matplotlib`
        
        ## Install:
        ```
        pip install tse_dataloader
        ```
        
        ## Functions:
        
        - Loading data with **get_data(ticker)** or **getcode_data(code)**
        
        ```
        >>> from tse_dataloader import download
        >>> MELT= download.get_data('ظˆط¨ظ…ظ„طھ')
        >>> print(MELT)
        
                           TICKER    FIRST     HIGH  ...     OPEN     LAST  date_shamsi
        Date                                         ...                               
        2009-02-18  S*Mellat.Bank   1050.0   1050.0  ...   1000.0   1050.0   1387/11/30
        2009-02-21  S*Mellat.Bank   1051.0   1076.0  ...   1050.0   1057.0   1387/12/03
        2009-02-22  S*Mellat.Bank   1065.0   1074.0  ...   1050.0   1055.0   1387/12/04
        2009-02-23  S*Mellat.Bank   1066.0   1067.0  ...   1065.0   1060.0   1387/12/05
        2009-02-25  S*Mellat.Bank   1061.0   1064.0  ...   1061.0   1060.0   1387/12/07
        ...                   ...      ...      ...  ...      ...      ...          ...
        2020-07-01  S*Mellat.Bank  27350.0  27370.0  ...  26110.0  26690.0   1399/04/11
        2020-07-04  S*Mellat.Bank  26940.0  27000.0  ...  26940.0  25600.0   1399/04/14
        2020-07-05  S*Mellat.Bank  24560.0  27040.0  ...  25760.0  25860.0   1399/04/15
        2020-07-06  S*Mellat.Bank  26200.0  26950.0  ...  25670.0  26950.0   1399/04/16
        2020-07-07  S*Mellat.Bank  27320.0  28200.0  ...  26860.0  26040.0   1399/04/17
        
        [2374 rows x 12 columns]
        
        >>> MELT= download.getcode_data(778253364357513)
        ```
        - Plot Close price and Volume line chart with **close_vol()**
        
        ```
        >>> from tse_dataloader import analysis
        >>> analysis.close_vol(MELT)
        
        # to create a chart without gaps you can use df.reset_index()
        >>> analysis.close_vol(MELT.reset_index())
        ```
        - Calculate short and long term Simple Moving Average, Exponential Moving Average, add them to your data frame and plot chart line with **sma()** and **ema()**
        
        ```
        >>> from tse_dataloader import analysis
        >>> analysis.sma(MELT, 20, 50)
        >>> analysis.ema(MELT, 20, 50)
        ```
        
        - For your convenience, I create a list of tickers and attached it to the package to load data faster. In order to update your symbol list, you can use **stock_list.update()**. it takes a few minutes to update data from tsetmc. 
        
        ```
        >>> import tse_dataloader
        >>> stock_list.update()
        
        Database has updated!
        ```
        
        - In some cases, if you couldn't find your specific symbol in the list, you can add it to the list manually with the **stock_list.add()** function.
        
        ```
        >>> import tse_dataloader
        >>> stock_list.add(2400322364771558, 'ط´ط³طھط§')
        
        
        Symbol added to the list!
        ```
        You can find every symbol's code at the end of its URL:   
        <a href="http://www.tsetmc.com/loader.aspx?ParTree=151311&i=2400322364771558">http://www.tsetmc.com/loader.aspx?ParTree=151311&i=</strong>2400322364771558</strong></a>
        
        
        
        Thanks to [tehran-stock](https://github.com/ghodsizadeh/tehran-stocks)
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
