Metadata-Version: 2.1
Name: DailyTrends
Version: 2.0
Summary: A package to receive full-scale daily Google Trends data
Home-page: https://github.com/le0x99/DailyTrends/
Author: Leonard Vorbeck
Author-email: leomxyy@googlemail.com
License: UNKNOWN
Description: #  ✨ DailyTrends ✨
        
        # **NOTE** : Overlap-Bug is now fixed and requesting data for multiple keywoards now works fine.
        This lightweight API solves the problem of getting only monthly-based data for large time series when collecting Google Trends data. No login required. For unlimited requests, I will implement a Tor-based solution soon.
        
        ### Installation
        
        ```bash
        $ pip install DailyTrends
        ```
        
        
        
        
        ### How to use
        
        ```ipython
        >>> from DailyTrends.collect import collect_data
        # Get the data directly into python.
        # The returned dataframe is already indexed and ready for storage/analysis.
        >>> data = collect_data("AMD stock",
                            save=False, verbose=False)                   
        >>> data.info()
        
        <class 'pandas.core.frame.DataFrame'>
        DatetimeIndex: 5666 entries, 2004-01-01 to 2019-07-06
        Freq: D
        Data columns (total 1 columns):
        AMD stock: (Worldwide)    5666 non-null float64
        dtypes: float64(1)
        memory usage: 88.5 KB
        
        #Plotting some rolling means of the daily data
        >>> ax=data.rolling(10).mean().plot();
            data.rolling(25).mean().plot(ax=ax);
            data.rolling(50).mean().plot(ax=ax)
        ```
        
        ![image.png](1.png)
        
        ### Add your own data
        ```ipython
        # In this case the actual historic prices of the stock
        >>> import pandas as pd
        >>> price_data = pd.read_csv("price_data.csv")
        >>> merged = pd.merge(price_data, data,
                          left_index=True, right_index=True)
        >>> merged[["AMD stock: (Worldwide)", "Open"]].rolling(30).mean().plot()
        ```
        ![image.png](2.png)
        
        ### Load multiple queries
        
        ```ipython
        >>> data = collect_data(["Intel", "AMD"],
                           save=False, verbose=False)      
                        
        ```
        
        
        
        
        ### To-Do
        
        - Add rescale capabilities
        - Optimze multi-query search by combining it to a single request
        - Add time range
        - Add Tor-Network-based requests
        - Add unique identifiers
        - Add tqdm
        - Prevent Null-Overlaps
        
        
        
        
        
        
        ## **Disclaimer**
        
        This API is not supported by Google and is for experimental purposes only.
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Description-Content-Type: text/markdown
