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I would like to remove the flat lines on my graph by keeping the labels x.

I have this code which gives me a picture

dates = df_stock.loc[start_date:end_date].index.values
x_values = np.array([datetime.datetime.strptime(d, "%Y-%m-%d %H:%M:%S") for d in dates])

fig, ax = plt.subplots(figsize=(15,9))

# y values
y_values = np.array(df_stock.loc[start_date:end_date, 'Bid'])
# plotting
_ = ax.plot(x_values, y_values, label='Bid')

# formatting
formatter = mdates.DateFormatter('%m-%d %H:%M')
ax.xaxis.set_major_formatter(formatter)

enter image description here

The flat lines correspond to data which does not exist I would like to know if it is possible not to display them while keeping the gap of the x labels.

thank you so much

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1 Answer 1

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3

You want to have time on the x-axis and time is equidistant -- independent whether you have data or not. You now have several options:

  1. don't use time on the x-axis but samples/index
  2. do as in 1. but change the ticks & labels to draw time again (but this time not equidistantly)
  3. make the value-vector equidistant and use NaNs to fill the gaps

Why is this so? Per default, matplotlib produces a line plot, which connects the points with lines using the order in which they are presented. In contrast to this a scatter plot just plots the individual points, not suggesting any underlying order. You achieve the same result as if you would use a line plot without markers.

In general, you have 3-4 options

  1. use the plot command but only plot markers (add linestyle='')
  2. use the scatter command.
  3. if you use NaNs, plotdoes not know what to plot and plots nothing (but also won't connect non-existing points with lines)
  4. use a loop and plot connected sections as separate lines in the same axes

options 1/2 are the easiest if you want to do almost no changes on your code. Option 3 is the most proper and 4 mimics this result.

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