Series collection
- from
- 1985-07-01=217
- to
- 2023-05-01=361
- min:
- 215
- max:
- 361
- avg:
- 275
- σ:
- 42.952
| Series code | 1985-07-01 | 1985-11-01 | 1988-10-01 | 1989-02-01 | 1990-01-01 | 1990-12-01 | 1991-08-01 | 1998-04-01 | 1998-07-01 | 1999-04-01 | 1999-07-01 | 1999-12-01 | 2001-05-01 | 2001-07-01 | 2004-07-01 | 2005-07-01 | 2006-07-01 | 2006-11-01 | 2007-07-01 | 2008-05-01 | 2008-07-01 | 2009-07-01 | 2011-01-01 | 2012-01-01 | 2012-07-07 | 2013-01-01 | 2021-10-01 | 2022-01-01 | 2022-05-01 | 2023-01-01 | 2023-05-01 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| [marche_travail.remuneration_dans_fonction_publique.indice_majore_minimal] | 217 | 215 | 219 | 220 | 221 | 224 | 226 | 247 | 249 | 250 | 252 | 253 | 258 | 261 | 263 | 275 | 279 | 280 | 283 | 288 | 290 | 292 | 295 | 302 | 308 | 309 | 340 | 343 | 352 | 353 | 361 |
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 = []
# Traitement minimum dans la fonction publique, en points d'indice majoré
df1 = fetch_series("IPP/taxbenefit_tables/marche_travail.remuneration_dans_fonction_publique.indice_majore_minimal")
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()