Metadata-Version: 2.1
Name: quantclean
Version: 0.0.1
Summary: Quantclean is a program that reformats every financial dataset to US Equity TradeBar
Home-page: https://github.com/ssantoshp/quantclean
Author: Santosh Passoubady
Author-email: santoshpassoubady@gmail.com
License: MIT
Description: # Quantclean 🧹
        
        <strong><em>"Make it cleaner, make it leaner"</em></strong>
        
        Already used by several people working in the quant and finance industries, Quantclean is the all-in-one tool that will help you to reformat your dataset and clean it.
        
        Quantclean is a program that **reformats** every financial dataset to **US Equity TradeBar** (Quantconnect format)
        
        We all faced the problem of reformating or data to a standard. Manual data cleaning is clearly boring and take time. Quantclean is here to help you and to make you life easier as a quant.
        
        Works great with datas from Quandl, Algoseek, Alpha Vantage, yfinance, and many other more...
        
        ## Few things you may want to know before getting started 🍉
        
        1) Even if you don't have an open, close, volume, high, low, date column, quantclean will create a blank column for it. No problem!
        
        2) The dataframe generated will look like this if you have a date and time column (or if both are on the same column):
        
        | Date| Open | High | Low | Close | Volume
        | ----------- | ---------- | --------- | ---------- | --------- | ---------
        | 20131001 09:00 | 6448000  | 6448000 | 6448000 | 6448000 | 90
        
         - Date - String date "YYYYMMDD HH:MM" in the timezone of the data format.
         - Open - Deci-cents Open Price for TradeBar.
         - High - Deci-cents High Price for TradeBar.
         - Low - Deci-cents Low Price for TradeBar.
         - Close - Deci-cents Close Price for TradeBar.
         - Volume - Number of shares traded in this TradeBar.
         
        
        3) You can also get something like that if use the ```sweeper_dash``` function instead of ```sweeper```
        
        
        | Date| Open | High | Low | Close | Volume
        | ----------- | ---------- | --------- | ---------- | --------- | ---------
        | **2013-10-01 09:00:00** | 6448000  | 6448000 | 6448000 | 6448000 | 90
        
        
        As you can see, the date format is YYYY-MM-DD and no more YYYYMMDD.
        
        
        4) If you just have a date column (e.g : something like YYYY-MM-DD), it will look like this:
        
        | Date| Open | High | Low | Close | Volume
        | ----------- | ---------- | --------- | ---------- | --------- | ---------
        | 20131001 | 6448000  | 6448000 | 6448000 | 6448000 | 90
        
        
        You can also use the ```sweeper_dash``` function here.
        
        ## How to use it? 🚀
        
        First, download the quantclean.py file in the folder where you are working
        
        <u>Note :</u> I took this data from Quandl, your dataset doesn't have to look like this one necessarily, quantclean adapts to your dataset as well as possible
        
        ```
        from quantclean import sweeper
        
        df = pd.read_csv('AS-N100.csv')
        df
        ```
        <img src="https://i.ibb.co/zVfYx5J/Capture.jpg"/>
        
        ```
        _df = sweeper(df)
        _df
        ```
        Output: 
        
        <img src="https://i.ibb.co/YdncjPz/Capture.jpg"/>
        
        Now, you may not be happy of this date colum which is presented in the YYYYMMDD format and maybe be prefer YYYY-MM-DD.
        
        In that case do :
        
        ```
        df_dash = sweeper_dash(df)
        df_dash
        ```
        
        Output: 
        
        <img src = "https://i.ibb.co/LNd5Kb9/Capture.jpg"/>
        
        ## Contribution
        
        If you have some suggestions or improvements don't hesitate to create an issue or make a pull request. Any help is welcome!
        
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