Series collection
[IPP/taxbenefit_tables/droits_mutation_titre_gratuit.abattement.arr_petits_enfants_donation] Abattement arrières-petits-enfants (donation uniquement)
- from
- 2006-01-01=5,000
- to
- 2013-01-01=5,310
- min:
- 5,000
- max:
- 5,310
- avg:
- 5,161.286
- σ:
- 127.112
| Series code | 2006-01-01 | 2008-01-01 | 2009-01-01 | 2010-01-01 | 2011-01-01 | 2012-01-01 | 2013-01-01 |
|---|---|---|---|---|---|---|---|
| [droits_mutation_titre_gratuit.abattement.arr_petits_enfants_donation] | 5000 | 5000 | 5065 | 5212 | 5232 | 5310 | 5310 |
Loading chart
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 = []
# Abattement arrières-petits-enfants (donation uniquement)
df1 = fetch_series("IPP/taxbenefit_tables/droits_mutation_titre_gratuit.abattement.arr_petits_enfants_donation")
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]))
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()