Series collection
- from
- 2004=13.89
- to
- 2013=NA
- min:
- 13.89
- max:
- 16.14
- avg:
- 14.953
- σ:
- 0.731
| Series code | 2004 | 2005 | 2006 | 2007 | 2008-12-01 | 2009-04-01 | 2010-04-01 | 2011-04-01 | 2012-04-01 |
|---|---|---|---|---|---|---|---|---|---|
| [retraites.independants.salref_rc_com] | 13.89 | 14.112 | 14.389 | 14.648 | 14.809 | 15.3 | 15.483 | 15.808 | 16.14 |
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 = []
# Salaire de référence du régime complémentaire des commerçants (valeur d'achat du point)
df1 = fetch_series("IPP/taxbenefit_tables/retraites.independants.salref_rc_com")
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()