Do not use a line graph for categorical data.

Then that is your takeaway. There is absolutely no need to use so much text and color. Choose a few key categories that are a good representation of people's overall shopping habits and add those as your colored lines. You can add another line with a neutral color combining all the rest and show the average values over time. Drop all the numbers from the chart and add a subtitle that says how nothing has changed despite this and that. And please use a logical order for the dates on the X axis.

There are a number of issues with this visualization, so I'll try to be concise. Please don't take it as a harsh criticism but more as a helpful learning moment.

Is there a key takeaway or two that you have identified and that you would like the audience to notice? At the moment I just don't see it because you're trying to fit so much information into one single visual that I don't know what I'm supposed to concentrate on. It looks like you got some data and put together a visual without much thought to what you're wanting to communicate or you didn't even think about any findings at all.

It looks like you're trying to show certain trends over time, but bar charts are not the best choice for this kind of data. You've tried to fit too much information into one single visual, but in reality it's just excessive text and color everywhere. When stacked bar charts are appropriate, you should use no more than 5 colors.

The time intervals appear really inconsistent. We want to see intervals like day, week, month, quarter or year, not jump from random dates to another as it's misleading and disruptive.

If your intention is to show trends over time, use an area or line chart instead. For example, an area chart showing the total (as opposed to a second bar), and lines showing different categories (as opposed to stacked bars). Now, instead of showing an excessive number of different colored lines, think what you are trying to communicate.

Option 1: Is it really necessary to show all these different categories separately if nothing really stands out and if it's so difficult to tell which is which due the high number of them? Combine them into no more than 5 bigger categories and draw attention to the most important or interesting ones by using distinctive colors, the uninteresting ones can all have the same neutral tone of grey for example.

Option 2: Are there any product categories with a very surprising or significant change in the trend? Let's say there is and you find that the sale of bread has skyrocketed since the pandemic began compared to all other categories combined. That would be your interesting finding to focus on, one line representing bread and another the rest. Color that line with one that stands out and leave the other one neutral. Everyone's eyes will be drawn immediately to the fact that there's an interesting trend with bread.

When choosing a color palette you should consider the type of data you're dealing with. For example, don't use a diverging color scheme intended for continuous data when the data is actually categorical. There may be cases when this may be appropriate, such as when the categories represent ordered levels but not when we're dealing with companies names. Also, avoid using the same colors to represent different things within the same visualization.