A helper library to pull data from netdata api into a pandas dataframe.

pypi package CI

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.

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_nice  system.cpu|guest  system.cpu|steal  \
time_idx                                                                
1600946808                      0                 0          0.000000   
1600946809                      0                 0          0.000000   
1600946810                      0                 0          0.000000   
1600946811                      0                 0          0.000000   
1600946812                      0                 0          0.251889   

            system.cpu|softirq  system.cpu|irq  system.cpu|user  \
time_idx                                                          
1600946808            0.251256               0         0.502513   
1600946809            0.000000               0         0.501253   
1600946810            0.000000               0         0.503778   
1600946811            0.250000               0         0.750000   
1600946812            0.000000               0         0.755668   

            system.cpu|system  system.cpu|nice  system.cpu|iowait  \
time_idx                                                            
1600946808           0.251256                0                  0   
1600946809           1.002506                0                  0   
1600946810           0.251889                0                  0   
1600946811           0.500000                0                  0   
1600946812           0.251889                0                  0   

            system.load|load1  system.load|load5  system.load|load15  
time_idx                                                              
1600946808                NaN                NaN                 NaN  
1600946809                NaN                NaN                 NaN  
1600946810               0.05               0.04                 0.0  
1600946811               0.05               0.04                 0.0  
1600946812               0.05               0.04                 0.0  

Examples

You can find some more examples in the examples folder.

Or if you just want to play with it right now you can use this Google Colab notebook to quickly get started.