Series collection
[IPP/taxbenefit_tables/marche_travail.salaire_minimum.minstage.taux_gratification_min] Gratification minimale d'un stagiaire (en % du Plafond de la Sécurité Sociale) - Marché du travail
- from
- 2008-02-01=0.125
- to
- 2015-09-01=0.15
- min:
- 0.125
- max:
- 0.15
- avg:
- 0.137
- σ:
- 0.01
| Series code | 2008-02-01 | 2015-01-01 | 2015-09-01 |
|---|---|---|---|
| [marche_travail.salaire_minimum.minstage.taux_gratification_min] | 0.125 | 0.1375 | 0.15 |
Loading chart
This Python snippet uses the DBnomics Python client to download the series of your cart and plot each of them with a line chart.
This is a starting point that you can customize. Plotly is used here, however any other chart library can be used.
You can start by copying it to a Jupyter Notebook , for example.
If you add series to your cart, you will need to copy-paste the new lines of the source code.
import plotly.express as px
import pandas as pd
from dbnomics import fetch_series
dfs = []
# Gratification minimale d'un stagiaire (en % du Plafond de la Sécurité Sociale) - Marché du travail
df1 = fetch_series("IPP/taxbenefit_tables/marche_travail.salaire_minimum.minstage.taux_gratification_min")
df1["series_id"] = df1[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df1)
# display(df1)
display(px.line(df1, x="period", y="value", title=df1.series_id[0]))
df_all = pd.concat(dfs)
fig = px.line(df_all, x="period", y="value", color="series_code", title="All the cart")
fig.update_layout(legend={"xanchor": "right", "yanchor": "bottom"})
fig.show()