Series collection
- from
- 1954-07-01=0.165
- to
- 2014=0.2
- min:
- 0.165
- max:
- 0.23
- avg:
- 0.194
- σ:
- 0.017
| Series code | 1954-07-01 | 1955-07-01 | 1968-12-01 | 1970 | 1972 | 1977 | 1982-07-01 | 1995-08-01 | 2000-04-01 | 2014 |
|---|---|---|---|---|---|---|---|---|---|---|
| [taxation_indirecte.tva.taux_normal] | 0.165 | 0.195 | 0.19 | 0.23 | 0.2 | 0.176 | 0.186 | 0.206 | 0.196 | 0.2 |
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 de la taxe sur la valeur ajoutée (TVA)
df1 = fetch_series("IPP/taxbenefit_tables/taxation_indirecte.tva.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()