Series collection
- from
- 1960=1
- to
- 2022=1.011
- min:
- 1
- max:
- 1.27
- avg:
- 1.054
- σ:
- 0.061
| Series code | 1960 | 1961 | 1962 | 1963 | 1964 | 1965 | 1966 | 1967 | 1968 | 1969 | 1970 | 1971 | 1972 | 1973 | 1974 | 1975 | 1976 | 1977 | 1978 | 1979 | 1980 | 1981 | 1982 | 1983 | 1984 | 1985 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2004 | 2005 | 2006 | 2007 | 2008 | 2008-09-01 | 2009-04-01 | 2010-04-01 | 2011-04-01 | 2012-04-01 | 2013-04-01 | 2014-10-01 | 2015-10-01 | 2016-10-01 | 2017-10-01 | 2018 | 2019 | 2020 | 2021 | 2022 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| [retraites.secteur_public.pension_civile.revalorisation_pension] | 1 | 1.26985598952651 | 1.20007302719189 | 1.1085855422118 | 1.05808847271553 | 1.04000732399524 | 1.05621025858415 | 1.08489698307579 | 1.15365025466893 | 1.10080598060974 | 1.11471354166667 | 1.10982658959538 | 1.08209538702111 | 1.1342674707343 | 1.18794774546987 | 1.17679147036945 | 1.15924116125323 | 1.11185682326622 | 1.09635599159075 | 1.13750498206457 | 1.13273137697517 | 1.11981799797776 | 1.06002143622722 | 1.05483323911815 | 1.04304245283019 | 1.02353651176826 | 1.02371794871795 | 1.03723404255319 | 1.02732240437158 | 1.01596113809854 | 1.03297491039427 | 1 | 1.01824817518248 | 1.01181683899557 | 1.02498107494322 | 1.0108275328693 | 1.01173708920188 | 1.00550747442958 | 1.02006420545746 | 1.02214930270714 | 1.01668056713928 | 1.015 | 1.02 | 1.018 | 1.018 | 1.011 | 1.008 | 1.01 | 1.009 | 1.021 | 1.021 | 1.013 | 1 | 1.001 | 1 | 1.008 | 1 | 1.003 | 1.01 | 1.004 | 1.011 |
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 = []
# Coefficient de revalorisation des pensions civiles
df1 = fetch_series("IPP/taxbenefit_tables/retraites.secteur_public.pension_civile.revalorisation_pension")
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()