Series collection
- from
- 2012=NA
- to
- 2014=NA
- min:
- 3,536
- max:
- 3,536
- avg:
- 3,536
- σ:
- 0
- from
- 2012=NA
- to
- 2014=NA
- min:
- 350
- max:
- 350
- avg:
- 350
- σ:
- 0
- from
- 2012=NA
- to
- 2014=NA
- min:
- 13,795
- max:
- 13,795
- avg:
- 13,795
- 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 = []
# Majoration du seuil par demi-part supplémentaire, de la réduction exceptionnelle d'impôts (2013)
df1 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.reduction_impot_exceptionnelle.majoration_seuil")
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]))
# Montant plafond par part pour les deux premières parts de la réduction exceptionnelle d'impôts (2013)
df2 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.reduction_impot_exceptionnelle.montant_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]))
# Seuil (à partir duquel la réduction décroît) par part pour les deux premières parts de la réduction exceptionnelle d'impôts
df3 = fetch_series("IPP/taxbenefit_tables/impot_revenu.calcul_reductions_impots.reduction_impot_exceptionnelle.seuil")
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]))
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()