pip install influxdb-client

import influxdb_client
import pandas as pd
import plotly.graph_objects as go
from influxdb_client.client.write_api import SYNCHRONOUS
from plotly.subplots import make_subplots

bucket = "ratp_bucket"
org = "ratp_org"
token = "z_4Ph73ntH1mobyqm6OJ5d6nYsM0qY8rZYIJs6bZpS0ioDW1VpujRG5l67xXV4dgAFlBgQB9681wPaft2Fp5cw=="
url = "http://localhost:8086"

client = influxdb_client.InfluxDBClient(url=url, token=token, org=org)

query = 'from(bucket:"ratp_bucket") \
          |> range(start: 2022-07-01, stop: 2022-08-31) \
          |> filter(fn:(r) => r._measurement == "qualite-air") \
          |> filter(fn:(r) => r.station == "chatelet") \
          |> filter(fn:(r) => r._field == "TEMP" or r._field == "HUMI") \
          |> pivot(rowKey:["_time"], columnKey: ["_field"], valueColumn: "_value")'

df = client.query_api().query_data_frame(org=org, query=query)

# modification de deux températures et humidités incohérentes par rapport aux valeurs voisines
df.loc[df["_time"] == "2022-07-31T00:00:00+02:00", "TEMP"] = float("NaN")
df.loc[df["_time"] == "2022-08-03T19:00:00+02:00", "TEMP"] = float("NaN")
df.loc[df["_time"] == "2022-07-31T00:00:00+02:00", "HUMI"] = float("NaN")
df.loc[df["_time"] == "2022-08-03T19:00:00+02:00", "HUMI"] = float("NaN")

# création du diagramme
url = "https://data.ratp.fr/explore/dataset/qualite-de-lair-mesuree-dans-la-station-chatelet/information/"
title = f"<b>Température & Humidité Station Châtelet\
<br>Juillet-Août 2022</b>\
<br>Source:<a href='{url}'>https://data.ratp.fr/</a>"

fig = make_subplots(specs=[[{"secondary_y": True}]])

# courbe de température sur l'axe y primaire
fig.add_trace(
    go.Scatter(
        mode="lines",
        x=df["_time"],
        y=df["TEMP"],
        name="Température en °C",
        line=dict(color="red", width=1),
    ),
    secondary_y=False,
)

# courbe d'humidité sur l'axe y secondaire
fig.add_trace(
    go.Scatter(
        mode="lines",
        x=df["_time"],
        y=df["HUMI"],
        name="Humidité en %",
        line=dict(color="blue", width=1),
    ),
    secondary_y=True,
)

# centrage du titre, couleur d'arrière plan, style et placement de la légende, hover label
fig.update_layout(
    title=title,
    title_x=0.5,
    plot_bgcolor="white",
    legend=dict(yanchor="top", y=1.1, xanchor="right", x=0.90, bgcolor="#efefef"),
    hovermode="x unified",
    hoverlabel=dict(
        bgcolor="white",
        bordercolor="red",
        namelength=500,
    ),
)

# légendes des 3 axes
fig.update_xaxes(
    title_text="Date",
    showgrid=False,
    showline=True,
    linecolor="black",
    linewidth=1,
)

fig.update_yaxes(
    title_text="Température en °C",
    secondary_y=False,
    color="red",
    showgrid=False,
    showline=True,
    linecolor="red",
    linewidth=1,
)

fig.update_yaxes(
    title_text="Humidité en %",
    secondary_y=True,
    color="blue",
    showgrid=False,
    showline=True,
    linecolor="blue",
    linewidth=1,
)

# affichage et sauvegarde
fig.show()
fig.write_html("influxdb-plotly.html")

client.close()