Series collection
- from
- 1975-01-01=NA
- to
- 2011-01-01=15,000
- min:
- 15,000
- max:
- 15,000
- avg:
- 15,000
- σ:
- 0
- from
- 2013-01-01=7,500
- to
- 2013-01-01=7,500
- min:
- 7,500
- max:
- 7,500
- avg:
- 7,500
- σ:
- 0
- from
- 1975-01-01=NA
- to
- 2020-01-01=1,000
- min:
- 400
- max:
- 2,100
- avg:
- 829.241
- σ:
- 586.877
- from
- 1975-01-01=NA
- to
- 2005-01-01=0.75
- min:
- 0.5
- max:
- 0.75
- avg:
- 0.628
- σ:
- 0.091
- from
- 2021=554
- to
- 2023=593
- min:
- 554
- max:
- 593
- avg:
- 569.667
- σ:
- 16.819
- from
- 1975-01-01=NA
- to
- 2019-01-01=1,000
- min:
- 1,000
- max:
- 1,000
- avg:
- 1,000
- σ:
- 0
- from
- 1975-01-01=NA
- to
- 2019-01-01=0.75
- min:
- 0.75
- max:
- 0.75
- avg:
- 0.75
- σ:
- 0
- from
- 1975=NA
- to
- 2002=0.2
- min:
- 0.01
- max:
- 0.2
- avg:
- 0.067
- σ:
- 0.068
- from
- 1975-01-01=NA
- to
- 2005-01-01=0.66
- min:
- 0.4
- max:
- 0.66
- avg:
- 0.54
- σ:
- 0.099
| Series code | 1988-01-01 | 1989-01-01 | 1990-01-01 | 1993-01-01 | 1994-01-01 | 1995-01-01 | 1996-01-01 | 1997-01-01 | 1998-01-01 | 1999-01-01 | 2000-01-01 | 2001-01-01 | 2002-01-01 | 2003-01-01 | 2004-01-01 | 2005-01-01 | 2006-01-01 | 2007-01-01 | 2008-01-01 | 2009-01-01 | 2010-01-01 | 2011-01-01 | 2013-01-01 | 2014-01-01 | 2015-01-01 | 2016-01-01 | 2017-01-01 | 2018-01-01 | 2019-01-01 | 2020-01-01 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| [impot_revenu.calcul_reductions_impots.dons.dons_aux_partis_politiques.plafond_foyer] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 15000 | - | - | - | - | - | - | - | - |
| [impot_revenu.calcul_reductions_impots.dons.dons_aux_partis_politiques.plafond_seul] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 7500 | - | - | - | - | - | - | - |
| [impot_revenu.calcul_reductions_impots.dons.dons_coluche.plafond] | 400 | 500 | 520 | 1000 | 1020 | 1040 | 2000 | 2030 | 2050 | 2070 | 2100 | 400 | 407 | 414 | 422 | 470 | 479 | 488 | 495 | 510 | 513 | 521 | - | 526 | 529 | 530 | 531 | 537 | 546 | 1000 |
| [impot_revenu.calcul_reductions_impots.dons.dons_coluche.taux] | 0.5 | - | - | - | - | - | 0.6 | - | - | - | - | - | - | 0.66 | - | 0.75 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| [impot_revenu.calcul_reductions_impots.dons.dons_notre_dame.plafond] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 1000 | - |
| [impot_revenu.calcul_reductions_impots.dons.dons_notre_dame.taux] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 0.75 | - |
| [impot_revenu.calcul_reductions_impots.dons.taux_reduction] | - | 0.4 | - | - | - | - | 0.5 | - | - | - | - | - | 0.6 | - | - | 0.66 | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| Series code | 1976 | 1987 | 1996 | 1999 | 2001 | 2002 | 2021 | 2022 | 2023 |
|---|---|---|---|---|---|---|---|---|---|
| [impot_revenu.calcul_reductions_impots.dons.dons_cultuels.plafond_dons] | - | - | - | - | - | - | 554 | 562 | 593 |
| [impot_revenu.calcul_reductions_impots.dons.plafond_dons] | 0.01 | 0.0125 | 0.0175 | 0.06 | 0.1 | 0.2 | - | - | - |
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 par foyer fiscal des dons et cotisations versés pour le financement des partis et groupements politiques
df1 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.dons.dons_aux_partis_politiques.plafond_foyer")
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 individuel des dons consentis aux partis politiques
df2 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.dons.dons_aux_partis_politiques.plafond_seul")
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]))
# Plafond des versements ouvrant droit à la réduction d'impôt sur le revenu (IR) au titre des dons faits aux organismes d'aide aux personnes en difficulté ("Dons Coluche")
df3 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.dons.dons_coluche.plafond")
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]))
# Taux de la réduction d'impôt sur le revenu (IR) au titre des dons faits aux organismes d'aide aux personnes en difficulté ("Dons Coluche")
df4 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.dons.dons_coluche.taux")
df4["series_id"] = df4[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df4)
# display(df4)
display(px.line(df4, x="period", y="value", title=df4.series_id[0]))
# Plafond des dépenses ouvrant à une réduction d'impôt de 75 % pour les dons aux associations cultuelles ou à un établissement public reconnu d'Alsace-Moselle
df5 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.dons.dons_cultuels.plafond_dons")
df5["series_id"] = df5[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df5)
# display(df5)
display(px.line(df5, x="period", y="value", title=df5.series_id[0]))
# Plafond
df6 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.dons.dons_notre_dame.plafond")
df6["series_id"] = df6[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df6)
# display(df6)
display(px.line(df6, x="period", y="value", title=df6.series_id[0]))
# Taux
df7 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.dons.dons_notre_dame.taux")
df7["series_id"] = df7[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df7)
# display(df7)
display(px.line(df7, x="period", y="value", title=df7.series_id[0]))
# Plafond (en % du revenu imposable) des dons pris en compte pour la réduction d'impôt sur le revenu (IR)
df8 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.dons.plafond_dons")
df8["series_id"] = df8[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df8)
# display(df8)
display(px.line(df8, x="period", y="value", title=df8.series_id[0]))
# Taux général de réduction d'impôt sur le revenu (IR) appliqué aux dons
df9 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.dons.taux_reduction")
df9["series_id"] = df9[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df9)
# display(df9)
display(px.line(df9, x="period", y="value", title=df9.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()