Series collection
- from
- 1977-12-31=0.5
- to
- 2022-S1=0.25
- min:
- 0.25
- max:
- 0.5
- avg:
- 0.355
- σ:
- 0.076
| Series code | 1977-12-31 | 1986-07-12 | 1988-S1 | 1989-07-14 | 1990-06-15 | 1991-06-24 | 1993-S1 | 2019-S1 | 2020-S1 | 2021-S1 | 2022-S1 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| [taxation_societes.impot_societe.taux_normal] | 0.5 | 0.45 | 0.42 | 0.39 | 0.37 | 0.34 | 0.3333 | 0.31 | 0.28 | 0.265 | 0.25 |
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 = []
# Taux normal
df1 = fetch_series("IPP/taxbenefit_tables/taxation_societes.impot_societe.taux_normal")
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()