Series collection
- from
- 1949=1.2
- to
- 2025=1.022
- min:
- 1
- max:
- 1.32
- avg:
- 1.051
- σ:
- 0.054
| Series code | 1949 | 1950 | 1951 | 1952-04-01 | 1953-04-01 | 1955-04-01 | 1956-04-01 | 1957-04-01 | 1958-04-01 | 1959-04-01 | 1960-04-01 | 1961-04-01 | 1962-04-01 | 1963-04-01 | 1964-04-01 | 1965-04-01 | 1966-04-01 | 1967-04-01 | 1968-04-01 | 1969 | 1969-04-01 | 1969-11-01 | 1970-04-01 | 1971-04-01 | 1972-04-01 | 1973-04-01 | 1974 | 1974-07-01 | 1975 | 1975-07-01 | 1976 | 1976-07-01 | 1977 | 1977-07-01 | 1978 | 1978-07-01 | 1979 | 1979-07-01 | 1980 | 1980-07-01 | 1981 | 1981-07-01 | 1982 | 1982-07-01 | 1983 | 1984 | 1984-07-01 | 1985 | 1985-07-01 | 1986 | 1986-10-01 | 1987 | 1987-07-01 | 1988 | 1988-07-01 | 1989-07-01 | 1990 | 1990-07-01 | 1991 | 1991-07-01 | 1992 | 1992-07-01 | 1993 | 1994 | 1995 | 1995-07-01 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2008-09-01 | 2009-04-01 | 2010-04-01 | 2011-04-01 | 2012-04-01 | 2013-04-01 | 2014-04-01 | 2015-10-01 | 2016-10-01 | 2017-10-01 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| [retraites.secteur_prive.regime_general_cnav.reval_s] | 1.2 | 1.32 | 1.16 | 1.1 | 1.2 | 1.09 | 1.085 | 1.12 | 1.075 | 1.135 | 1.105 | 1.077 | 1.15 | 1.16 | 1.12 | 1.11 | 1.069 | 1.058 | 1.056 | 1.04 | 1.0435 | 1.03 | 1.119 | 1.101 | 1.115 | 1.109 | 1.082 | 1.067 | 1.063 | 1.096 | 1.083 | 1.082 | 1.086 | 1.071 | 1.082 | 1.044 | 1.065 | 1.04 | 1.054 | 1.064 | 1.067 | 1.062 | 1.067 | 1.074 | 1.04 | 1.018 | 1.022 | 1.034 | 1.028 | 1.013 | 1.005 | 1.018 | 1.01 | 1.026 | 1.013 | 1.012 | 1.0215 | 1.013 | 1.017 | 1.008 | 1.01 | 1.018 | 1.013 | 1.02 | 1.012 | 1.005 | 1.02 | 1.012 | 1.011 | 1.012 | 1.005 | 1.022 | 1.022 | 1.015 | 1.017 | 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 | 1.015 | 1.01 | 1.004 | 1.011 | 1.008 | 1.053 | 1.022 |
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 salaires portés aux comptes
df1 = fetch_series("IPP/taxbenefit_tables/retraites.secteur_prive.regime_general_cnav.reval_s")
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()