Series collection
- from
- 1978-01-01=3,000
- to
- 2022-01-01=3,500
- min:
- 2,300
- max:
- 15,000
- avg:
- 6,678.889
- σ:
- 4,455.31
- from
- 1978-01-01=0
- to
- 2006-01-01=0.5
- min:
- 0
- max:
- 0.5
- avg:
- 0.25
- σ:
- 0.204
| Series code | 1978-01-01 | 1983-01-01 | 1984-01-01 | 1985-01-01 | 1986-01-01 | 1988-01-01 | 1991-01-01 | 2001-01-01 | 2006-01-01 | 2022-01-01 |
|---|---|---|---|---|---|---|---|---|---|---|
| [impot_revenu.credits_impots.gardenf.plafond] | 3000 | 4000 | 4310 | 5000 | 10000 | 13000 | 15000 | 2300 | - | 3500 |
| [impot_revenu.credits_impots.gardenf.taux] | 0 | - | - | - | - | 0.25 | - | - | 0.5 | - |
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 des dépenses effectivement supportées pour la garde des enfants âgés de moins de six ans qu'ils ont à leur charge pour le calcul du crédit d’impôt
df1 = fetch_series("IPP/taxbenefit_tables/impot_revenu.credits_impots.gardenf.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 du crédit d'impôt pour frais de garde d'enfants à charge âgés de moins de six ans
df2 = fetch_series("IPP/taxbenefit_tables/impot_revenu.credits_impots.gardenf.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]))
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()