Series collection
- from
- 1996-04-01=100,000
- to
- 2013-01-01=31,865
- min:
- 15,000
- max:
- 100,000
- avg:
- 44,643
- σ:
- 30,010.953
| Series code | 1996-04-01 | 1997-01-01 | 2002-01-01 | 2003-01-01 | 2008-01-01 | 2009-04-09 | 2011-01-01 | 2012-01-01 | 2013-01-01 |
|---|---|---|---|---|---|---|---|---|---|
| [droits_mutation_titre_gratuit.abattement.petits_enfants_donation] | 100000 | 100000 | 15000 | 30000 | 30390 | 31272 | 31395 | 31865 | 31865 |
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 petits-enfants (donation uniquement)
df1 = fetch_series("IPP/taxbenefit_tables/droits_mutation_titre_gratuit.abattement.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()