index.qmd

---
title: "Public civil servant and inflation rate in France"
---

In the file [fonctionnaires_pauvres.py](fonctionnaires_pauvres.py) we investigated the evolution of the salary of civil servants in France through the "Point d'indice" evolution.


```{python}
#| echo: false
#| warning: false
import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
# import seaborn as sns
# import matplotlib.pylab as plt
import numpy as np
import pooch
import zipfile
#| echo: false
import datetime
from dateutil.relativedelta import relativedelta

# Source: # https://www.insee.fr/fr/statistiques/serie/001763852

current_time = datetime.datetime.now()
last_date = current_time - relativedelta(months=2)
fname_inflation = pooch.retrieve(f"https://www.insee.fr/fr/statistiques/serie/telecharger/csv/001763852?ordre=antechronologique&transposition=donneescolonne&periodeDebut=1&anneeDebut=1990&periodeFin={last_date.month}&anneeFin={last_date.year}&revision=sansrevisions", known_hash=None)

zf = zipfile.ZipFile(fname_inflation)
# Open a subdirectory where the 'valeurs_mensuelles.csv file is located


for file in zf.namelist():
    if 'valeurs_mensuelles.csv' in file:
        with zf.open(file, 'r') as f:
            df_ipc = pd.read_csv(f, header=0, sep=";",skiprows=4)
        break

```

```{python}
#| echo: false
#| layout-ncol: 1

df_ipc.columns = ["Date", "IPC", "Useless", "Date2"]
df_ipc.index = pd.to_datetime(df_ipc["Date"], format="%Y-%m")
df_ipc.drop(df_ipc.columns[[0, 2]], inplace=True, axis=1)
df_ipc.head()

# Set origin
init_date = "2005-09-01"
df_ipc["IPC(idx)"] = df_ipc["IPC"] / df_ipc.loc[init_date]["IPC"]
df_ipc.head()
# Sort by "Date" in ascending order
df_ipc.sort_values(by="Date", inplace=True)
```

```{python}
#| echo: false
#| warning: false
fname_pt_indice = pooch.retrieve("https://www.data.gouv.fr/fr/datasets/r/6b5a3e7e-7de7-437c-b8eb-a04ab4138fbb", known_hash=None)

df_pt_idx = pd.read_csv(fname_pt_indice, usecols=["date_effet", "valeur_100_points_euros"])

df_pt_idx = df_pt_idx.rename(columns={"date_effet": "Date", "valeur_100_points_euros": "Point d'indice"})

df_pt_idx["Date"] = pd.to_datetime(df_pt_idx["Date"], format="%Y-%m-%d")

df_pt_idx.sort_values(by="Date", inplace=True)


df = pd.merge_asof(df_ipc, df_pt_idx, on="Date")
df.index = df["Date"]


df.loc[init_date]["Point d'indice"]
df["Point d'indice(idx)"] = (
    df["Point d'indice"] / df.loc[init_date]["Point d'indice"]
)

df["Point d'indice(euros constant)"] = (
    df["Point d'indice(idx)"] / df["IPC(idx)"]
)
```


```{python}
#| echo: false
#| layout-ncol: 1


fig = go.Figure()

fig.add_trace(go.Scatter(x=df["Date"], y=df["IPC(idx)"], mode='lines', name='IPC(idx)'))
fig.add_trace(go.Scatter(x=df["Date"], y=df["Point d'indice(idx)"], mode='lines', name="Point d'indice(idx)"))

fig.update_layout(
# style white:
    template="simple_white",
    title="Joint evolution of inflation and point d'indice <br> Réference 1 le " + init_date,
    xaxis=dict(
        range=[init_date, df['Date'].iloc[-1]],
        tickangle=-60,
        nticks=15,
        tickformat='%Y'
    ),
    hovermode="x unified",
    legend=dict(
        yanchor="top",
        y=0.99,
        xanchor="left",
        x=0.01
    )
)

fig.update_traces(hovertemplate="%{x|%Y/%m} value: %{y}")

```


```{python}
#| echo: false
#| layout-ncol: 1

fig = go.Figure()

fig.add_trace(go.Scatter(x=df["Date"], y=df["Point d'indice(euros constant)"], mode='lines', name="Point d'indice(euros constant)"))

fig.update_layout(
    template="simple_white",
    title="Point d'indice (corrigé de l'inflation): <br> Réference 1 le " + init_date,
    xaxis=dict(
        range=[init_date, df['Date'].iloc[-1]],
        tickangle=-60,
        nticks=15,
        tickformat='%Y'
    ),
    yaxis=dict(
        range=[0.80, 1.2]
    ),
    hovermode="x unified",
    legend=dict(
        yanchor="top",
        y=0.9,
        xanchor="left",
        x=0.1
    )
)

fig.update_traces(hovertemplate="%{x|%Y/%m} value: %{y}")

# matplotlib version
# df.plot(
#     x="Date",
#     y=["Point d'indice(euros constant)"],
#     title="Point d'indice (€ corrigé de l'inflation):\n Réference 1 le "
#     + init_date,
# )
# ax = plt.gca()
# ax.set_xlim(left=np.datetime64(init_date))
# ax.set_ylim(bottom=0.80, top=1.2)
# ax.legend().remove()

```


```{python}
#| echo: false
print(f"Computation was performed at : {current_time} (GMT)")
```

Sources are:

- inflation : [https://www.insee.fr/fr/statistiques/serie/001763852#Telechargement](https://www.insee.fr/fr/statistiques/serie/001763852#Telechargement)
- point d'indice: [https://www.data.gouv.fr/fr/datasets/r/6b5a3e7e-7de7-437c-b8eb-a04ab4138fbb](https://www.data.gouv.fr/fr/datasets/r/6b5a3e7e-7de7-437c-b8eb-a04ab4138fbb)