## Description
This is a Python library based on *beautifulsoup4*, *pandas* &
*mplfinance*.
<br> You may use it to download price history and fundamental information of companies from
Dhaka Stock Exchange and Chittagong Stock Exchange.
<br>This can assist you to create further analyses
based on fundamental and price history data.
<br>Also create Candlestick charts to analyse the price history of stocks using
this easy-to-use wrapper for mplfinance.
## Installation
```
pip install stocksurferbd
```
## Usage
#### Downloading historical price data of a single stock-
```python
from stocksurferbd import PriceData
loader = PriceData()
loader.save_history_csv(symbol='ACI', file_name='ACI_history.csv', market='DSE')
```
The above code will create a file named- `ACI_history.csv`.
It'll contain historical price data for ACI Limited in Dhaka Stock Exchange (DSE).
There are 3 parameters for this method-
1. ```symbol``` : Provide stock symbol of the company as string.
2. ```file_name``` : Provide the name of the history data file as string.
3. ```market```: Provide the market name as string from which you want to download the data.
Probable values are ```'CSE'``` and ```'DSE'```
#### Downloading current market price data of all listed companies in DSE/CSE-
```python
from stocksurferbd import PriceData
loader = PriceData()
loader.save_current_csv(file_name='current_data.csv', market='DSE')
```
The above code will create a file named- `current_history.csv` in the current folder.
It'll contain current price data for all symbols.
There are 2 parameters for this method-
1. ```file_name``` : Provide the name of the current price data file as string.
2. ```market```: Provide the market name as string from which you want to download the data.
Probable values ar ```'CSE'``` and ```'DSE'```
#### Downloading fundamental data for a list of companies available in DSE-
```python
from stocksurferbd import FundamentalData
loader = FundamentalData()
loader.save_company_data('ACI', path='company_info')
```
The above code will create two files named `ACI_company_data.csv` &
`ACI_financial_data.csv` in the `company_info` folder relative to
current directory. The file named `ACI_company_data.csv` contains
the fundamental data of ACI Limited for the current year and
`ACI_financial_data.csv` contains year-wise fundamental data according to [DSE website](http://dsebd.org).
There are 2 parameters `save_company_data()` this method-
1. ```symbol``` : Provide stock symbol of the company as string.
2. ```path``` : Provide the name of the directory as string to save the company data.
#### Create Candlestick charts for analyzing price history-
```python
from stocksurferbd import CandlestickPlot
cd_plot = CandlestickPlot(csv_path='ACI_history.csv', symbol='ACI')
cd_plot.show_plot(
xtick_count=120,
resample=True,
step='3D'
)
```
The above code will create a Candlestick plot like the ones provided by
Stock broker trading panels.
<br/>There are 2 parameters ```__init__()``` method of CandlestickPlot class-
1. ```csv_path``` : Provide the path of history csv file as string to generate plot
2. ```symbol``` : Provide stock symbol of the company as string.
<br/>There are also 3 parameters show_plot() method-
1. ```xtick_count``` : Provide an integer value.
It sets the count of how many recent data points needs to be plotted.
2. ```resample``` : Provide boolean ```True``` or ```False```.
Set ```True``` if you want to plot daily data aggregated by multiple days.
3. ```step```: Only Active when ```resample=True```.
Valid values are in the form-
```'3D'``` and ```'7D'``` for 3 days plots and weekly plots respectively.
The following are some example images of Candlestick plots-
<br><br>
## If you want to contribute
Any contribution would be highly appreciated. Kindly go through the
[guidelines for contributing](CONTRIBUTING.md).
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