Series collection
- from
- 1979-S2=10,000
- to
- 2020-08-01=1,594
- min:
- 1,500
- max:
- 10,000
- avg:
- 2,745.429
- σ:
- 2,961.908
| Series code | 1979-S2 | 1984-S1 | 2002-S1 | 2003-08-02 | 2005-S1 | 2006-S1 | 2007-S1 | 2008-S1 | 2009-S1 | 2010-04-30 | 2010-S1 | 2011-06-11 | 2013-S1 | 2020-08-01 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| [droits_mutation_titre_gratuit.abattement.autre_succession] | 10000 | 10000 | 1500 | 1500 | 1500 | 1500 | 1500 | 1500 | 1520 | 1570 | 1564 | 1594 | 1594 | 1594 |
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 autres individus (succession)
df1 = fetch_series("IPP/taxbenefit_tables/droits_mutation_titre_gratuit.abattement.autre_succession")
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()