Series collection
- from
- 2018=6,000
- to
- 2023=NA
- min:
- 6,000
- max:
- 6,255
- avg:
- 6,135.4
- σ:
- 84.599
- from
- 2018=8,000
- to
- 2023=NA
- min:
- 8,000
- max:
- 8,340
- avg:
- 8,180.6
- σ:
- 112.807
- from
- 2018=27,000
- to
- 2023=NA
- min:
- 27,000
- max:
- 28,150
- avg:
- 27,609.8
- σ:
- 381.419
| Series code | 2018 | 2019 | 2020 | 2021 | 2022 |
|---|---|---|---|---|---|
| [taxe_habitation.degrevement_d_office.plaf_rfr_degrev.autres_demi_parts_supp] | 6000 | 6096 | 6157 | 6169 | 6255 |
| [taxe_habitation.degrevement_d_office.plaf_rfr_degrev.deux_premieres_demi_parts_supp] | 8000 | 8128 | 8210 | 8225 | 8340 |
| [taxe_habitation.degrevement_d_office.plaf_rfr_degrev.premiere_part] | 27000 | 27432 | 27706 | 27761 | 28150 |
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 de revenu fiscal de référence pour le dégrèvement d'office à taux plein pour autres demi-parts supplémentaires
df1 = fetch_series("IPP/taxbenefit_tables/taxe_habitation.degrevement_d_office.plaf_rfr_degrev.autres_demi_parts_supp")
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]))
# Plafond de revenu fiscal de référence pour le dégrèvement d'office à taux plein - deux premières demi-parts supplémentaires
df2 = fetch_series("IPP/taxbenefit_tables/taxe_habitation.degrevement_d_office.plaf_rfr_degrev.deux_premieres_demi_parts_supp")
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]))
# Plafonds de revenu fiscal de référence pour le dégrèvement d'office à taux plein - 1ère part
df3 = fetch_series("IPP/taxbenefit_tables/taxe_habitation.degrevement_d_office.plaf_rfr_degrev.premiere_part")
df3["series_id"] = df3[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df3)
# display(df3)
display(px.line(df3, x="period", y="value", title=df3.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()