Series collection
[IPP/taxbenefit_tables/taxe_habitation.maj_seuil_valeur_locative_abattement_condition_modeste] Majoration par personne à charge du pourcentage plafond de la valeur locative par rapport à la valeur locative moyenne pour bénéficier de l'abattement pour personnes de condition modeste
- from
- 2017-01-01=0.1
- to
- 2023-01-01=NA
- min:
- 0.1
- max:
- 0.1
- avg:
- 0.1
- σ:
- 0
| Series code | 2017-01-01 |
|---|---|
| [taxe_habitation.maj_seuil_valeur_locative_abattement_condition_modeste] | 0.1 |
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 = []
# Majoration par personne à charge du pourcentage plafond de la valeur locative par rapport à la valeur locative moyenne pour bénéficier de l'abattement pour personnes de condition modeste
df1 = fetch_series("IPP/taxbenefit_tables/taxe_habitation.maj_seuil_valeur_locative_abattement_condition_modeste")
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()