Livechart API + Data Science packages

Version 0

Pandas and Plotly

Providing a straightforward way to analyse data, these packages are widely used in machine learning.
Pandas is one of the most used libraries for data manipulation: https://pandas.pydata.org
Plotly http://plotly.com is a package for interactive data visualization, here how to get it work with jupyter lab

API Quick how-to

The service URL is nds.iaea.org/relnsd/v0/data? followed by parameters. For example:
nds.iaea.org/relnsd/v0/data?fields=decay_rads&nuclides=241am&rad_types=g.
The API v0 guide gives the detailed description, but the examples below are self explanatory

Examples

First import the libraries and set the Livechart API service

import pandas as pd
import plotly.express as px
import plotly.graph_objects as go

# the service URL
livechart = "https://nds.iaea.org/relnsd/v0/data?"

! Warning !

There have been cases in which the service returns an HTTP Error 403: Forbidden
In this case use the following workaround

import urllib.request

def lc_read_csv(url):
    req = urllib.request.Request(url)
    req.add_header('User-Agent', 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:77.0) Gecko/20100101 Firefox/77.0')
    return pd.read_csv(urllib.request.urlopen(req))

Plot γ energy vs intensity for Am-241 decay

fields=decay_rads specifies to retrieve the decay radiations, nuclides=241am specifies the parent of the decay (241am), rad_types=g for the radiation type (gamma).
On the plot below, mouseover the points to see the data. Zoom an pan are enabled, and the option to save as png is is activated when the mouse is over the top-right

# load data into a dataframe 

# this loading might not work, then use the line below
#df = pd.read_csv(livechart + "fields=decay_rads&nuclides=241am&rad_types=g")
df = lc_read_csv(livechart + "fields=decay_rads&nuclides=241am&rad_types=g")

df = df[pd.to_numeric(df['intensity'],errors='coerce').notna()] # remove blanks (unknown intensities)
df.intensity = df['intensity'].astype(float) # convert to numeric. Note how one can specify the field by attribute or by string 

fig = px.scatter(df, x="energy", y="intensity", log_y=True) # plot in log scale
fig.show()