Series collection
[IPP/taxbenefit_tables/retraites.independants.salref_rci] Valeur annuelle d'acquisition du point du régime complémentaire des indépendants (valeur d'achat du point)"
- from
- 2013-01-01=17.309
- to
- 2023-01-01=19.394
- min:
- 17.309
- max:
- 19.394
- avg:
- 17.801
- σ:
- 0.637
| Series code | 2013-01-01 | 2015-10-01 | 2017-10-01 | 2019-01-01 | 2020-01-01 | 2021-01-01 | 2022-01-01 | 2023-01-01 |
|---|---|---|---|---|---|---|---|---|
| [retraites.independants.salref_rci] | 17.309 | 17.324 | 17.456 | 17.515 | 17.691 | 17.765 | 17.956 | 19.394 |
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 = []
# Valeur annuelle d'acquisition du point du régime complémentaire des indépendants (valeur d'achat du point)"
df1 = fetch_series("IPP/taxbenefit_tables/retraites.independants.salref_rci")
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()