Series collection
- from
- 2001-01-01=5,100
- to
- 2018-01-01=2,450
- min:
- 2,450
- max:
- 5,100
- avg:
- 3,775
- σ:
- 1,325
- from
- 2001-01-01=0.3
- to
- 2001-01-01=0.3
- min:
- 0.3
- max:
- 0.3
- avg:
- 0.3
- σ:
- 0
- from
- 2001-01-01=6,700
- to
- 2018-01-01=4,050
- min:
- 4,050
- max:
- 6,700
- avg:
- 5,375
- σ:
- 1,325
- from
- 2001-01-01=0.4
- to
- 2001-01-01=0.4
- min:
- 0.4
- max:
- 0.4
- avg:
- 0.4
- 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 = []
# Plafond maximal d'abattement DOM - Guadeloupe, Martinique, Réunion
df1 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_impot_revenu.plaf_qf.abat_dom.guadeloupe_martinique_reunion.plaf")
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 d'abattement DOM - Guadeloupe, Martinique, Réunion
df2 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_impot_revenu.plaf_qf.abat_dom.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]))
# Plafond maximal d'abattement DOM - Guyane, Mayotte
df3 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_impot_revenu.plaf_qf.abat_dom.guyane_mayotte.plaf")
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 d'abattement DOM - Guyane, Mayotte
df4 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_impot_revenu.plaf_qf.abat_dom.guyane_mayotte.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]))
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()