Python matplotlib – Combine categorical background along with scatter plot

I am trying to figure out a right library in Python to create a complex plot which looks something like this: The plot background is classified into 3 regions (Yellow, Red, Green) based on conditions …

For loop for assigning colors to a plot python

I am working on a for loop to assign numbers to the classes and I am successful in that but I find it hard to simultaneously insert different colors based on the number of classes using the same for …

How to correctly shift the baseline in an area plot to a particular y location and change the fill color correspondingly, in Altair?

I wanted to be able to do something like this – NOTE: The horizontal line you see is NOT at y=0, but y=1 But using color or fill encoding with condition does not really work in area charts. The …

Ploting multiple curves (x, y1, y2, x, y3, y4) in the same plot

I’m trying to plot a graph with four different values on the “y” axis. So, I have 6 arrays, 2 of which have elements that represent the time values ​​of the “x” axis and the other 4 represent the corresponding elements (in the same position) in relation to the “y” axis. Example: The coordinates of the “LT” graph are: And with these coordinates, I can generate a graph with two “y” axes, which contains the points (-110,-113,-3,-5) and an “x” axis with the points (’18:14:17.566′, ’18:14:17.570′). Similarly, it is possible to do the same “GNR” arrays. So, how can I

Is there a way to visualise time series data in such a way that on x-axis i get ticks in year-month format in python?

I am trying to plot a data of stock close price for each day but on the x-axis, i get no labels on xtick instead of year-month format I tried to take the “Date” and “Close Price” column in a separate dataframe and then tried plotting them. I have dataframe similar to this Answer Just covert it with pandas to_datetime() function

Seaborn Catplot set values over the bars

I plotted a catplot in seaborn like this g = sns.catplot(x=’year’, y=’income’, data=df, kind=’bar’, hue=’geo_name’, legend=True) g.fig.set_size_inches(15,8) g.fig.subplots_adjust(top=0.81,right=0.86) …