Series collection
- from
- 1981-10-01=0.074
- to
- 2010-S2=0.012
- min:
- 0
- max:
- 0.083
- avg:
- 0.019
- σ:
- 0.016
| Series code | 1981-10-01 | 1982-04-01 | 1983-04-01 | 1984-04-01 | 1984-10-01 | 1985-S1 | 1986-10-01 | 1986-S1 | 1986-S2 | 1987-S1 | 1987-S2 | 1988-S1 | 1988-S2 | 1989-S2 | 1990-S1 | 1990-S2 | 1991-S1 | 1991-S2 | 1992-S1 | 1992-S2 | 1993-S1 | 1994-S1 | 1995-S1 | 1995-S2 | 1996-S1 | 1997-S1 | 1998-S1 | 1999-S1 | 2000-S1 | 2001-S1 | 2003-S1 | 2004-S1 | 2005-S1 | 2006-S1 | 2007-S2 | 2008-S2 | 2009-S2 | 2010-S2 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| [chomage.preretraites.sr_fne.revalorisation_sr] | 0.0743 | 0.0831 | 0.04 | 0.018 | 0.022 | 0.028 | 0.005 | 0.013 | 0 | 0.018 | 0.01 | 0.026 | 0.013 | 0.012 | 0.0215 | 0.013 | 0.017 | 0.008 | 0.01 | 0.018 | 0.013 | 0.02 | 0.012 | 0.005 | 0.02 | 0.012 | 0.011 | 0.012 | 0.005 | 0.022 | 0.015 | 0.017 | 0.02 | 0.018 | 0.0195 | 0.025 | 0.01 | 0.012 |
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 = []
# Revalorisation du salaire de référence pour le calcul des allocations de préretraites FNE-ARPE
df1 = fetch_series("IPP/taxbenefit_tables/chomage.preretraites.sr_fne.revalorisation_sr")
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()