Metadata-Version: 2.1
Name: netdata_pandas
Version: 0.0.37
Summary: A helper library for pulling data from netdata into a pandas dataframe.
Home-page: https://github.com/netdata/netdata-pandas/tree/master/
Author: Andrew Maguire
Author-email: andrewmaguire@netdata.cloud
License: Apache Software License 2.0
Description: # netdata-pandas
        > A helper library to pull data from netdata api into a pandas dataframe.
        
        
        [![pypi package](https://img.shields.io/pypi/v/netdata-pandas.svg)](https://pypi.python.org/pypi/netdata-pandas/) 
        [![CI](https://github.com/netdata/netdata-pandas/workflows/CI/badge.svg)](https://github.com/netdata/netdata-pandas/actions?query=workflow%3ACI)
        
        ## Install
        
        `pip install netdata-pandas`
        
        ## Documentation
        
        More detailed documentation can be found at https://netdata.github.io/netdata-pandas
        
        ## Quickstart
        
        Get some data into a pandas dataframe.
        
        ```python
        from netdata_pandas.data import get_data
        
        df = get_data('london.my-netdata.io', ['system.cpu','system.load'], after=-60, before=0)
        print(df.shape)
        print(df.head())
        ```
        
            (60, 12)
                        system.cpu|guest  system.cpu|guest_nice  system.cpu|iowait  \
            time_idx                                                                 
            1604928205               0.0                    0.0                0.0   
            1604928206               0.0                    0.0                0.0   
            1604928207               0.0                    0.0                0.0   
            1604928208               0.0                    0.0                0.0   
            1604928209               0.0                    0.0                0.0   
            
                        system.cpu|irq  system.cpu|nice  system.cpu|softirq  \
            time_idx                                                          
            1604928205             0.0              0.0                 0.0   
            1604928206             0.0              0.0                 0.0   
            1604928207             0.0              0.0                 0.0   
            1604928208             0.0              0.0                 0.0   
            1604928209             0.0              0.0                 0.0   
            
                        system.cpu|steal  system.cpu|system  system.cpu|user  \
            time_idx                                                           
            1604928205          0.000000           0.501253         0.501253   
            1604928206          0.000000           0.753769         0.502513   
            1604928207          0.000000           0.505050         0.505050   
            1604928208          0.000000           0.751880         0.501253   
            1604928209          0.251256           0.251256         0.502513   
            
                        system.load|load1  system.load|load15  system.load|load5  
            time_idx                                                              
            1604928205               0.03                 0.0               0.04  
            1604928206               0.03                 0.0               0.04  
            1604928207               0.03                 0.0               0.04  
            1604928208               0.03                 0.0               0.04  
            1604928209               0.03                 0.0               0.04  
        
        
        An alternative way to call `get_data()` is to define what hosts and charts you want via the `host_charts_dict` param:
        
        ```python
        # define list of charts for each host you want data for
        host_charts_dict = {
            "london.my-netdata.io" : ['system.io','system.ip'],
            "newyork.my-netdata.io" : ['system.io','system.net'],
        }
        df = get_data(host_charts_dict=host_charts_dict, host_prefix=True)
        print(df.shape)
        print(df.head())
        ```
        
            (61, 8)
                        london.my-netdata.io::system.io|in  \
            time_idx                                         
            1604928340                                 NaN   
            1604928341                                 0.0   
            1604928342                                 0.0   
            1604928343                                 0.0   
            1604928344                                 0.0   
            
                        london.my-netdata.io::system.io|out  \
            time_idx                                          
            1604928340                                  NaN   
            1604928341                            -53.89722   
            1604928342                            -26.10278   
            1604928343                              0.00000   
            1604928344                              0.00000   
            
                        london.my-netdata.io::system.ip|received  \
            time_idx                                               
            1604928340                                       NaN   
            1604928341                                  49.25227   
            1604928342                                 227.22840   
            1604928343                                 123.56787   
            1604928344                                  31.99060   
            
                        london.my-netdata.io::system.ip|sent  \
            time_idx                                           
            1604928340                                   NaN   
            1604928341                             -51.85469   
            1604928342                             -85.22854   
            1604928343                             -43.00154   
            1604928344                             -19.55536   
            
                        newyork.my-netdata.io::system.io|in  \
            time_idx                                          
            1604928340                                  0.0   
            1604928341                                  0.0   
            1604928342                                  0.0   
            1604928343                                  0.0   
            1604928344                                  0.0   
            
                        newyork.my-netdata.io::system.io|out  \
            time_idx                                           
            1604928340                              0.000000   
            1604928341                             -6.545929   
            1604928342                             -9.454071   
            1604928343                              0.000000   
            1604928344                              0.000000   
            
                        newyork.my-netdata.io::system.net|received  \
            time_idx                                                 
            1604928340                                   13.778033   
            1604928341                                   18.281470   
            1604928342                                   24.811770   
            1604928343                                   26.406000   
            1604928344                                   26.457510   
            
                        newyork.my-netdata.io::system.net|sent  
            time_idx                                            
            1604928340                               -16.97193  
            1604928341                               -19.23857  
            1604928342                               -76.86994  
            1604928343                              -165.55492  
            1604928344                              -115.83034  
        
        
        ## Examples
        
        You can find some more examples in the [examples](https://github.com/netdata/netdata-pandas/tree/master/examples) folder. 
        
        Or if you just want to play with it right now you can use [this Google Colab notebook](https://colab.research.google.com/drive/1SGF3Ij1r8gNJOwdk-3cVhCvyUGwGiTnc?usp=sharing) to quickly get started.
        
Keywords: netdata pandas
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
