Series collection
- from
- 1978-01-01=NA
- to
- 2018-01-01=2,450
- min:
- 2,450
- max:
- 35,261
- avg:
- 25,624.688
- σ:
- 9,556.003
- from
- 1978-01-01=0.3
- to
- 1978-01-01=0.3
- min:
- 0.3
- max:
- 0.3
- avg:
- 0.3
- σ:
- 0
- from
- 1978-01-01=NA
- to
- 2018-01-01=4,050
- min:
- 4,050
- max:
- 45,566
- avg:
- 33,791.625
- σ:
- 12,337.865
- from
- 1978-01-01=0.4
- to
- 1978-01-01=0.4
- min:
- 0.4
- max:
- 0.4
- avg:
- 0.4
- σ:
- 0
- from
- 2013-01-01=6,700
- to
- 2018-01-01=4,050
- min:
- 4,050
- max:
- 6,700
- avg:
- 5,375
- σ:
- 1,325
- from
- 2013-01-01=0.4
- to
- 2013-01-01=0.4
- min:
- 0.4
- max:
- 0.4
- avg:
- 0.4
- σ:
- 0
| Series code | 1978-01-01 | 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 | 2001-01-01 | 2013-01-01 | 2018-01-01 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| [impot_revenu.calcul_reductions_impots.reduction_domtom.guadeloupe_martinique_reunion.plafond] | NA | 18000 | 20500 | 23100 | 25300 | 27230 | 28760 | 29450 | 30430 | 31230 | 32270 | 33303 | 34301 | 35261 | 33310 | 5100 | - | 2450 |
| [impot_revenu.calcul_reductions_impots.reduction_domtom.guadeloupe_martinique_reunion.taux] | 0.3 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| [impot_revenu.calcul_reductions_impots.reduction_domtom.guyane.plafond] | NA | 24000 | 27300 | 30700 | 33500 | 36050 | 38070 | 38990 | 40280 | 41330 | 42700 | 43035 | 44325 | 45566 | 44070 | 6700 | - | 4050 |
| [impot_revenu.calcul_reductions_impots.reduction_domtom.guyane.taux] | 0.4 | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - |
| [impot_revenu.calcul_reductions_impots.reduction_domtom.mayotte.plafond] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 6700 | 4050 |
| [impot_revenu.calcul_reductions_impots.reduction_domtom.mayotte.taux] | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | - | 0.4 | - |
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 = []
# Montant maximal de la réduction d'impôt sur le revenu pour les DOM en Guadeloupe, Martinique et à la Réunion
df1 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.reduction_domtom.guadeloupe_martinique_reunion.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 pour les DOM en Guadeloupe, Martinique et à la Réunion
df2 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.reduction_domtom.guadeloupe_martinique_reunion.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]))
# Montant maximal de la réduction d'impôt de la réduction d'impôt sur le revenu pour la Guyane
df3 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.reduction_domtom.guyane.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 de la réduction d'impôt sur le revenu pour la Guyane
df4 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.reduction_domtom.guyane.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]))
# Montant maximal de la réduction d'impôt sur le revenu pour la Mayotte
df5 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.reduction_domtom.mayotte.plafond")
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 la réduction d'impôt sur le revenu pour la Mayotte
df6 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.reduction_domtom.mayotte.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]))
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()