Series collection
- from
- 1983=205
- to
- 2020-08-01=178.44
- min:
- 142.85
- max:
- 223.75
- avg:
- 179.464
- σ:
- 22.098
- from
- 1983=268.41
- to
- 2020-08-01=202.32
- min:
- 161.97
- max:
- 294.5
- avg:
- 225.888
- σ:
- 39.153
- from
- 1983=331.82
- to
- 2016-08-01=NA
- min:
- 219.22
- max:
- 365.25
- avg:
- 293.828
- σ:
- 43.731
- from
- 1983=40.5
- to
- 2020-08-01=103.44
- min:
- 22.73
- max:
- 103.44
- avg:
- 44.504
- σ:
- 25.711
- from
- 1983=80.36
- to
- 2020-08-01=128.52
- min:
- 57.79
- max:
- 128.52
- avg:
- 79.155
- σ:
- 19.112
- from
- 1983=141.59
- to
- 2020-08-01=153.48
- min:
- 90.34
- max:
- 153.48
- avg:
- 125.558
- σ:
- 15.921
| Series code | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 | 1993 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2001 | 2002 | 2003 | 2004 | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2012-07-23 | 2013 | 2013-08-01 | 2014 | 2014-11-01 | 2015 | 2015-08-01 | 2016 | 2016-08-01 | 2017-08-01 | 2018-02-01 | 2018-08-01 | 2019-06-01 | 2019-08-01 | 2020-02-01 | 2020-08-01 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| [tarifs_energie.tarifs_reglementes_edf.tarif_fixe_base_edf_ttc.tarif_fixe_12_kva] | 205 | 217.77 | 223.75 | 220.54 | 218.65 | 215.01 | 202.26 | 186.74 | 186.8 | 188.48 | 193.51 | 198.29 | 198.28 | 200.21 | 197.02 | 193.72 | 167.33 | 164.88 | 164.46 | 166.77 | 169.44 | 172.1 | 172.32 | 173.72 | 176.02 | 173.82 | 161.82 | 142.85 | 148.13 | 153.7 | - | 171.49 | - | 176.28 | - | 176.28 | - | 180.08 | 144.93 | 143.46 | 150.93 | 150.93 | 164.79 | 167.04 | 178.44 |
| [tarifs_energie.tarifs_reglementes_edf.tarif_fixe_base_edf_ttc.tarif_fixe_15_kva] | 268.41 | 285.52 | 294.5 | 290.36 | 288.95 | 284.84 | 268.75 | 247.63 | 247.19 | 249.25 | 257.04 | 264.09 | 264.15 | 266.73 | 260.35 | 253.61 | 218.25 | 214.91 | 214.34 | 217.31 | 220.81 | 224.32 | 224.59 | 226.34 | 229.24 | 220.4 | 192.97 | 164.86 | 171.05 | 177.6 | - | 196.7 | - | 202.23 | - | 202.23 | - | 206.54 | 165.29 | 161.97 | 170.87 | 170.87 | 185.87 | 188.16 | 202.32 |
| [tarifs_energie.tarifs_reglementes_edf.tarif_fixe_base_edf_ttc.tarif_fixe_18_kva] | 331.82 | 353.28 | 365.25 | 360.2 | 359.24 | 354.66 | 335.25 | 317.67 | 309.86 | 310.02 | 320.56 | 329.88 | 330.03 | 333.26 | 323.68 | 313.51 | 269.16 | 264.93 | 264.22 | 267.84 | 272.19 | 276.54 | 276.85 | 278.96 | 282.44 | 267 | 238.82 | 219.22 | 227.44 | - | 233.87 | - | 235.52 | - | 239.34 | - | 233.83 | NA | - | - | - | - | - | - | - |
| [tarifs_energie.tarifs_reglementes_edf.tarif_fixe_base_edf_ttc.tarif_fixe_3_kva] | 40.5 | 32.36 | 27.09 | 26.23 | 26.04 | 25.62 | 24.11 | 23.98 | 24.89 | 25.52 | 25.68 | 25.82 | 25.74 | 25.99 | - | - | 22.74 | 22.73 | 22.8 | 23.16 | 23.51 | 23.86 | 23.9 | 24.12 | 24.51 | 42.33 | 68.03 | 64.95 | 67.4 | 69.37 | - | 51.7 | - | 53.28 | - | 53.28 | - | 54.42 | 66.83 | 68.82 | 91.89 | 91.89 | 97.63 | 99.48 | 103.44 |
| [tarifs_energie.tarifs_reglementes_edf.tarif_fixe_base_edf_ttc.tarif_fixe_6_kva] | 80.36 | 81.58 | 79.81 | 78.34 | 76.03 | 73.62 | 67.89 | 63.96 | 65.18 | 66.08 | 65.42 | 65.6 | 65.42 | 66.06 | - | - | 57.79 | - | 57.98 | 58.96 | 59.87 | 60.78 | 60.84 | 61.34 | 62.27 | 68.86 | 79.6 | 77.45 | 80.37 | 82.98 | - | 84.05 | - | 86.49 | - | 86.49 | - | 88.39 | 99.92 | 107.08 | 110.55 | 110.55 | 119.72 | 121.68 | 128.52 |
| [tarifs_energie.tarifs_reglementes_edf.tarif_fixe_base_edf_ttc.tarif_fixe_9_kva] | 141.59 | 150.01 | 152.99 | 150.7 | 148.36 | 145.19 | 135.76 | 125.84 | 126.41 | 127.72 | 129.98 | 132.5 | 132.4 | 133.69 | - | 133.82 | 116.42 | 114.85 | 114.57 | 116.23 | 118.06 | 119.88 | 120.06 | 121.1 | 122.81 | 112.76 | 96.84 | 90.34 | 93.77 | 96.97 | - | 111.33 | - | 114.64 | - | 114.64 | - | 117.17 | 117.31 | 125.08 | 130.37 | 130.37 | 142.07 | 144.24 | 153.48 |
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 = []
# Tarif fixe - 12 kVA
df1 = fetch_series("IPP/taxbenefit_tables/tarifs_energie.tarifs_reglementes_edf.tarif_fixe_base_edf_ttc.tarif_fixe_12_kva")
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]))
# Tarif fixe - 15 kVA
df2 = fetch_series("IPP/taxbenefit_tables/tarifs_energie.tarifs_reglementes_edf.tarif_fixe_base_edf_ttc.tarif_fixe_15_kva")
df2["series_id"] = df2[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df2)
# display(df2)
display(px.line(df2, x="period", y="value", title=df2.series_id[0]))
# Tarif fixe - 18 kVA
df3 = fetch_series("IPP/taxbenefit_tables/tarifs_energie.tarifs_reglementes_edf.tarif_fixe_base_edf_ttc.tarif_fixe_18_kva")
df3["series_id"] = df3[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df3)
# display(df3)
display(px.line(df3, x="period", y="value", title=df3.series_id[0]))
# Tarif fixe - 3 kVA
df4 = fetch_series("IPP/taxbenefit_tables/tarifs_energie.tarifs_reglementes_edf.tarif_fixe_base_edf_ttc.tarif_fixe_3_kva")
df4["series_id"] = df4[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df4)
# display(df4)
display(px.line(df4, x="period", y="value", title=df4.series_id[0]))
# Tarif fixe - 6 kVA
df5 = fetch_series("IPP/taxbenefit_tables/tarifs_energie.tarifs_reglementes_edf.tarif_fixe_base_edf_ttc.tarif_fixe_6_kva")
df5["series_id"] = df5[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df5)
# display(df5)
display(px.line(df5, x="period", y="value", title=df5.series_id[0]))
# Tarif fixe - 9 kVA
df6 = fetch_series("IPP/taxbenefit_tables/tarifs_energie.tarifs_reglementes_edf.tarif_fixe_base_edf_ttc.tarif_fixe_9_kva")
df6["series_id"] = df6[["provider_code", "dataset_code", "series_code"]].agg('/'.join, axis=1)
dfs.append(df6)
# display(df6)
display(px.line(df6, x="period", y="value", title=df6.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()