Series collection
- from
- 1977=NA
- to
- 1979=NA
- min:
- 2,000
- max:
- 2,000
- avg:
- 2,000
- σ:
- 0
- from
- 1977=NA
- to
- 1979=NA
- min:
- 16,000
- max:
- 16,000
- avg:
- 16,000
- σ:
- 0
- from
- 1977=NA
- to
- 1979=NA
- min:
- 3,720
- max:
- 3,720
- avg:
- 3,720
- σ:
- 0
- from
- 1977=NA
- to
- 1979=NA
- min:
- 1,860
- max:
- 1,860
- avg:
- 1,860
- σ:
- 0
- from
- 1977=NA
- to
- 1979=NA
- min:
- 23,000
- max:
- 23,000
- avg:
- 23,000
- σ:
- 0
- from
- 1977=NA
- to
- 1979=NA
- min:
- 37,000
- max:
- 37,000
- avg:
- 37,000
- 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 = []
# Montant de l'abattement exceptionnel en faveur de certains contribuables seuls pour le calcul du revenu imposable
df1 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.abat_exceptionnel.en_faveur_certains_contribuables_seuls_1.abattement")
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]))
# Maximum revenu net global de l'abattement exceptionnel en faveur de certains contribuables seuls pour le calcul du revenu imposable
df2 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.abat_exceptionnel.en_faveur_certains_contribuables_seuls_1.maximum_revenu_net_global")
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 1 de l'abattement exceptionnel en faveur des personnes âgées ou invalides pour le calcul du revenu imposable
df3 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.abat_exceptionnel.en_faveur_personnes_agees_invalides_2.abattement_1")
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 2 de l'abattement exceptionnel en faveur des personnes âgées ou invalides pour le calcul du revenu imposable
df4 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.abat_exceptionnel.en_faveur_personnes_agees_invalides_2.abattement_2")
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]))
# Seuil 1 de revenu net global pour l'abattement exceptionnel en faveur des personnes âgées ou invalides pour le calcul du revenu imposable
df5 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.abat_exceptionnel.en_faveur_personnes_agees_invalides_2.seuil_1_revenu_net_global")
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]))
# Seuil 2 de revenu net global pour l'abattement exceptionnel en faveur des personnes âgées ou invalides pour le calcul du revenu imposable
df6 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_revenus_imposables.abat_exceptionnel.en_faveur_personnes_agees_invalides_2.seuil_2_revenu_net_global")
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()