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Tag: matplotlib

How to plot aggregated by date pandas dataframe

I have this dataframe To aggregate payout_value by date I use: How do I plot (bar chart) dates on x-axis and aggregated payout sum on y axis? I tried using df.plot(x=’date’, y=’payout_value’,kind=”bar”) approach, but there is no ‘date’ column in df_daily dataframe, print(list(df_daily)) gives [(‘payout_value’, ‘sum’)] Answer you are almost there, use reset_index and plot your by df_daily

Matplotlib’s FuncAnimation calls init_func more than once

The documentation for matplotlib.animation.FuncAnimation says: init_func : […] This function will be called once before the first frame. But whenever I use FuncAnimation, the init_func is called multiple times. You can see this by adding a print statement to the basic example from Matplotlib’s website: Apart from producing a lovely plot, it immediately gives the standard output: If I keep

Why do my google tiles look poor in a Cartopy map?

I am a bit puzzled by the rendering of google tiles with Cartopy. The map looks extremely poor compared to the standard google map look. Example (code from https://ocefpaf.github.io/python4oceanographers/blog/2015/06/22/osm/): Generates: Which looks very poor—look at the pixelated rendering of text label and street number—compared to the same image shown on the linked website: Changing zoom level does not seem to

Automated cross stich pattern

I’m trying to create a cross stitch pattern with python as shown in the attached image. So far I simply have the pixilated image. I could import it in excel and manually add the grid and colors etc. But how can I ‘easily’ automate this in python? Can I use any of the normal figure plotting functions (pyplot), or should

Pandas.plot Multiple plot same figure

I have multiple CSV files that I am trying to plot in same the figure to have a comparison between them. I already read some information about pandas problem not keeping memory plot and creating the new one every time. People were talking about using an ax var, but I do not understand it… For now I have: But it’s

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