Series collection
- from
- 1999=NA
- to
- 2001=30,500
- min:
- 30,500
- max:
- 200,000
- avg:
- 115,250
- σ:
- 84,750
- from
- 2000-01-01=0.25
- to
- 2000-01-01=0.25
- min:
- 0.25
- max:
- 0.25
- avg:
- 0.25
- σ:
- 0
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 = []
# Plafond des versements de sommes d'argent et l'attribution de biens ou de droits effectués en exécution de la prestation compensatoire pris en compte dans le calcul de la réduction de l'impôt sur le revenu (IR)
df1 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.prestations_compensatoires.plafond")
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]))
# Taux de la réduction d'impôt sur le revenu (IR) sur les prestations compensatoires
df2 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.prestations_compensatoires.taux")
df2["series_id"] = df2[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df2)
# display(df2)
display(px.line(df2, x="period", y="value", title=df2.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()