Series collection
- from
- 1979-10-01=22
- to
- 1994-07-01=74.01
- min:
- 22
- max:
- 74.01
- avg:
- 57.299
- σ:
- 16.721
| Series code | 1979-10-01 | 1981-10-01 | 1983-10-01 | 1984-04-01 | 1984-10-01 | 1985-04-01 | 1985-10-01 | 1986-07-01 | 1987-04-01 | 1987-10-01 | 1990-01-01 | 1991-01-01 | 1991-07-01 | 1992-01-01 | 1992-07-01 | 1993-01-01 | 1994-07-01 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| [chomage.allocations_assurance_chomage.afd.montant_base] | 22 | 30.23 | 37.8 | 40 | 41.4 | 43 | 63 | 64.48 | 66.8 | 67.94 | 68.29 | 69.45 | 70.07 | 70.71 | 71.98 | 72.92 | 74.01 |
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 = []
# Montant de base de l'allocation de fin de droits
df1 = fetch_series("IPP/taxbenefit_tables/chomage.allocations_assurance_chomage.afd.montant_base")
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()