dcc.Markdown("**Daily** is the daily reconstructed OP from the regression model. **Monthly** (mean or median) are the monthly aggregated mean or median for each station. **Quaterly** is the seasonal (4 seasons: DJF, MAM, JJA, SON) mean or median aggratation per station. This plot may take some time to generate..."),
dcc.Markdown("""
**Daily** is the daily reconstructed OP from the
regression model. You have to chose only one station from
the little dropdown above. The default one is "CHAM".
**Monthly** (mean or median) are the monthly aggregated mean or median for each station. **Quaterly** is the seasonal (4 seasons: DJF, MAM, JJA, SON) mean or median aggratation per station. This plot may take some time to generate...
The bars represent the contribution of each source to
the OP (in nmol.min⁻¹.m⁻³) and the line and dot are the
observed OP.
"""),
dcc.Loading(
dcc.Graph(
id="op-contribution-ts-graph",
...
...
@@ -756,18 +798,18 @@ def plot_ts(df, station, var, groupby):