Cognite Charts: Figure element formatting for export

Here is a screenshot of a PNG export in Charts. It is in practice just a screenshot of the Charts interface. 

• The list of TSs is not relevant, and especially not the invisible TSs.
• The labels are too small and have a too low contrast
• I would like to change the granularity of the displayed TS to show some peaks that are hidden by the averager.
• Legend missing
• Difficult to check a value for one month, since the tick labels are year only.

As a comparison, here is a figure made in Python with matplotlib.

tag2 = "pi:112558"
tag1 = "pi:112556"

start = datetime(2016, 1, 1)
end = datetime(2022, 11, 1)
granularity = "1d"

data = client.datapoints.retrieve(external_id=[tag1, tag2], start=start, end=end, granularity=granularity, aggregates=["average"]).to_pandas()
data.columns = ["Upstream", "Downstream"]
data["dP"] = data.Upstream - data.Downstream

fig, ax = plt.subplots(figsize=(7, 3), dpi=200)

ax.plot(data.dP, color="black", lw=1, label="dP (1d avg)")
ax.axvline(datetime(2020, 11, 11), color="salmon", ls="-", lw=0.75, label="Endring til ~61 bar", zorder=1)

ax.grid(ls=":", lw=0.5)
#ax.set_ylim(40, 65)
#ax.set_xlabel("Dato")
ax.set_ylabel("dP (bar)")
ax.tick_params("x", labelrotation=45)
ax.set_xticklabels(ax.get_xticklabels(), ha="right")
ax.legend(bbox_to_anchor=(0.5, 1.0), loc="lower center", ncol=2)

ax.xaxis.set_major_locator(mdates.MonthLocator(interval=6))
ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%b"))

fig.tight_layout()
fig.savefig("dP_first_stage_separator.png")

Thanks @Anders Brakestad for taking the time to provide these examples and best practices! You’re absolutely right that we can (and should) have a more robust image exporting experience when you want to make your charts report/ presentation-ready. 

@Magdalena Rut FYI for some great suggestions and benchmarks for improving this feature.