Series collection
- from
- 1942-01-01=NA
- to
- 2006-01-01=NA
- min:
- 22,380
- max:
- 144,400
- avg:
- 95,855
- σ:
- 41,909.756
- from
- 1942-01-01=NA
- to
- 2006-01-01=NA
- min:
- 111,900
- max:
- 722,000
- avg:
- 479,275
- σ:
- 209,548.778
- from
- 1942-01-01=NA
- to
- 2006-01-01=NA
- min:
- 0.1
- max:
- 0.2
- avg:
- 0.16
- σ:
- 0.039
- from
- 1942-01-01=NA
- to
- 2023-01-01=4,321
- min:
- 3,160
- max:
- 31,900
- avg:
- 13,082.178
- σ:
- 10,918.659
- from
- 1942-01-01=NA
- to
- 2023-01-01=442
- min:
- 323
- max:
- 2,080
- avg:
- 940.393
- σ:
- 765.096
- from
- 1943-01-01=0.1
- to
- 1943-01-01=0.1
- min:
- 0.1
- max:
- 0.1
- avg:
- 0.1
- σ:
- 0
- from
- 1942=NA
- to
- 2023=14,171
- min:
- 12,000
- max:
- 200,000
- avg:
- 41,416.244
- σ:
- 35,810.932
- from
- 1942-01-01=NA
- to
- 2023-01-01=495
- min:
- 364
- max:
- 2,350
- avg:
- 1,110.688
- σ:
- 850.84
- from
- 1942-01-01=NA
- to
- 2018-01-01=NA
- min:
- 797
- max:
- 5,140
- avg:
- 1,766
- σ:
- 1,703.036
- from
- 1943-01-01=0.1
- to
- 1943-01-01=0.1
- min:
- 0.1
- max:
- 0.1
- avg:
- 0.1
- σ:
- 0
- from
- 1979-07-01=0.7
- to
- 1979-07-01=0.7
- min:
- 0.7
- max:
- 0.7
- avg:
- 0.7
- σ:
- 0
- from
- 1979-07-01=0.5
- to
- 1979-07-01=0.5
- min:
- 0.5
- max:
- 0.5
- avg:
- 0.5
- σ:
- 0
- from
- 1979-07-01=0.4
- to
- 1979-07-01=0.4
- min:
- 0.4
- max:
- 0.4
- avg:
- 0.4
- σ:
- 0
- from
- 1979-07-01=0.3
- to
- 1979-07-01=0.3
- min:
- 0.3
- max:
- 0.3
- avg:
- 0.3
- σ:
- 0
Series code | 1943-01-01 | 1953-01-01 | 1954-01-01 | 1959-01-01 | 1960-01-01 | 1973-01-01 | 1974-01-01 | 1975-01-01 | 1977-01-01 | 1978-01-01 | 1979-01-01 | 1979-07-01 | 1980-01-01 | 1981-01-01 | 1982-01-01 | 1983-01-01 | 1984-01-01 | 1985-01-01 | 1986-01-01 | 1987-01-01 | 1988-01-01 | 1989-01-01 | 1990-01-01 | 1991-01-01 | 1992-01-01 | 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 | 2013-01-01 | 2014-01-01 | 2015-01-01 | 2016-01-01 | 2017-01-01 | 2018-01-01 | 2019-01-01 | 2020-01-01 | 2021-01-01 | 2022-01-01 | 2023-01-01 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[impot_revenu.calcul_revenus_imposables.deductions.abat_supp.max] | - | - | - | - | - | 56000 | 62000 | 68000 | 72000 | - | - | - | 82000 | 92000 | - | - | 99000 | 104600 | 107200 | 110800 | 113800 | 117600 | 121400 | 125200 | 128800 | 131400 | 133400 | 136000 | 138600 | 140200 | 141400 | 142200 | 144400 | 22380 | 22780 | 23180 | 23580 | 24020 | NA | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
[impot_revenu.calcul_revenus_imposables.deductions.abat_supp.salaire_plafond] | - | - | - | - | - | 280000 | 310000 | 340000 | 360000 | - | - | - | 410000 | 460000 | - | - | 495000 | 523000 | 536000 | 554000 | 569000 | 588000 | 607000 | 626000 | 644000 | 657000 | 667000 | 680000 | 693000 | 701000 | 707000 | 711000 | 722000 | 111900 | 113900 | 115900 | 117900 | 120100 | NA | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
[impot_revenu.calcul_revenus_imposables.deductions.abat_supp.taux] | - | 0.1 | 0.15 | 0.19 | 0.2 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | NA | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
[impot_revenu.calcul_revenus_imposables.deductions.abatpen.max] | - | - | - | - | - | - | - | - | 5000 | 6000 | 6700 | - | 7600 | 8700 | 9800 | 21400 | 23100 | 24400 | 25000 | 25900 | 26600 | 27500 | 28400 | 29300 | 30200 | 30800 | 31300 | 31900 | 28000 | 24000 | 20000 | 20100 | 20400 | 3160 | 3214 | 3269 | 3325 | 3385 | 3446 | 3491 | 3592 | 3606 | 3660 | 3689 | 3707 | 3711 | 3715 | 3752 | 3812 | 3850 | 3858 | 3912 | 4123 | 4321 |
[impot_revenu.calcul_revenus_imposables.deductions.abatpen.min] | - | - | - | - | - | - | - | - | - | 1800 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 1860 | 1900 | 1930 | 1960 | 2000 | 2020 | 2040 | 2050 | 2080 | 323 | 328 | 334 | 340 | 346 | 352 | 357 | 367 | 368 | 374 | - | 379 | - | - | 383 | 389 | 393 | 394 | 400 | 422 | 442 |
[impot_revenu.calcul_revenus_imposables.deductions.abatpen.taux] | 0.1 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
[impot_revenu.calcul_revenus_imposables.deductions.abatpro.min] | - | - | - | - | - | - | - | - | 1500 | 1800 | - | - | - | - | - | - | - | - | - | - | - | - | 2000 | 2060 | 2120 | 2160 | 2190 | 2230 | 2270 | 2290 | 2310 | 2320 | 2350 | 364 | 370 | 376 | 382 | 389 | 396 | 401 | 413 | 415 | 421 | 424 | 426 | - | - | 430 | 437 | 441 | 442 | 448 | 472 | 495 |
[impot_revenu.calcul_revenus_imposables.deductions.abatpro.min2] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 5000 | 5040 | 5070 | 5140 | 797 | 811 | 825 | 839 | 854 | 869 | 880 | 906 | 910 | 924 | 931 | 936 | 937 | 938 | 947 | NA | - | - | - | - | - |
[impot_revenu.calcul_revenus_imposables.deductions.abatpro.taux] | 0.1 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
[impot_revenu.calcul_revenus_imposables.deductions.abatviag.taux1] | - | - | - | - | - | - | - | - | - | - | - | 0.7 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
[impot_revenu.calcul_revenus_imposables.deductions.abatviag.taux2] | - | - | - | - | - | - | - | - | - | - | - | 0.5 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
[impot_revenu.calcul_revenus_imposables.deductions.abatviag.taux3] | - | - | - | - | - | - | - | - | - | - | - | 0.4 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
[impot_revenu.calcul_revenus_imposables.deductions.abatviag.taux4] | - | - | - | - | - | - | - | - | - | - | - | 0.3 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
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 = []
# Abattement maximal de la déduction supplémentaire de 20%
df1 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abat_supp.max")
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]))
# Salaire plafond pour toucher la déduction supplémentaire de 20%
df2 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abat_supp.salaire_plafond")
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]))
# Taux de l'abattement
df3 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abat_supp.taux")
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]))
# Montant maximum pour l'ensemble du foyer de l'abattement sur les pensions
df4 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abatpen.max")
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]))
# Montant minimum par bénéficiaire de l'abattement sur les pensions
df5 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abatpen.min")
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]))
# Taux de l'abattement forfaitaire sur les pensions ou retraites
df6 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abatpen.taux")
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]))
# Montant maximum de la déduction forfaitaire pour frais professionnels
df7 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abatpro.max")
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]))
# Montant minimum (Cas général) de la déduction forfaitaire pour frais professionnels
df8 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abatpro.min")
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]))
# Montant minimum (Demandeur d'emploi) de la déduction forfaitaire pour frais professionnels
df9 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abatpro.min2")
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]))
# Taux de l'abattement forfaitaire sur les salaires pour frais professionels
df10 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abatpro.taux")
df10["series_id"] = df10[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df10)
# display(df10)
display(px.line(df10, x="period", y="value", title=df10.series_id[0]))
# Fraction imposable de la rente viagère à titre onéreux pour les personnes de moins de 50 ans
df11 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abatviag.taux1")
df11["series_id"] = df11[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df11)
# display(df11)
display(px.line(df11, x="period", y="value", title=df11.series_id[0]))
# Fraction imposable de la rente viagère à titre onéreux pour les personnes âgées de 50 à 59 ans
df12 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abatviag.taux2")
df12["series_id"] = df12[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df12)
# display(df12)
display(px.line(df12, x="period", y="value", title=df12.series_id[0]))
# Fraction imposable de la rente viagère à titre onéreux pour les personnes âgées de 60 à 69 ans
df13 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abatviag.taux3")
df13["series_id"] = df13[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df13)
# display(df13)
display(px.line(df13, x="period", y="value", title=df13.series_id[0]))
# Fraction imposable de la rente viagère à titre onéreux pour les personnes âgées de plus de 70 ans
df14 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.deductions.abatviag.taux4")
df14["series_id"] = df14[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df14)
# display(df14)
display(px.line(df14, x="period", y="value", title=df14.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()