11/29/2023 0 Comments Seaborn scatter plot axis range![]() ax.t_major_locator(())) and is probably the preferred way to set ticklabels but the post above offers a quick fix for a common error. Xticklabels=ax.get_xticklabels()) # <- OKįor this specific case, and is more flexible (e.g. If you need to change the ticklabel frequency along with tick frequency using the old ticklabels, using set_xticks and set_xticklabels one after the other throws a ValueError that looks like the following: ValueError: The number of FixedLocator locations (5), usually fromĪ call to set_ticks, does not match the number of labels (3).Ī way get around the issue is to use set() method to set the two simultaneously. If this stepsize based solution doesn't fit, then one can also populate the values of sparse_xticks or sparse_yticks at irregular intervals, if that is what is desired. Sparse_yticks = yĪx.set_xticklabels(sparse_xticks, fontsize=6) # set sparse xtick valuesĪx.set_yticklabels(sparse_yticks, fontsize=6) # set sparse ytick valuesĭepending on the usecase, one can adapt the above code simply by changing show_every and using that for sampling tick values for X or Y or both the axes. ![]() # here, we show every third value from `x` and `y` Now, we clean up the clutter with a new plot that shows only a sparse set of values on both x and y axes as ticks. # Note the super cluttered ticks on both X and Y axis. Here is a sample piece of code that produces cluttered ticks on both X and Y axes. Since None of the above solutions worked for my usecase, here I provide a solution using None (pun!) which can be adapted to a wide variety of scenarios. Notice the x-axis has integer values all evenly spaced by 5, whereas the y-axis has a different interval (the matplotlib default behavior, because the ticks weren't specified). Sample Usage import matplotlib.pyplot as plt Print(list(computeTicks(series, step = 100))) XMax, xMin = math.ceil(max(x)), math.floor(min(x))ĭMax, dMin = xMax + abs((xMax % step) - step) + (step if (xMax % step != 0) else 0), xMin - abs((xMin % step)) X - Required - A list-like object of integers or floats Here's a runnable example: import numpy as npĪx.t_ticks(np.arange(start, end, 0.712123))Īx.t_major_formatter(ticker.FormatStrFormatter('%0.1f'))īelow's a pure python implementation of the desired functionality that handles any numeric series (int or float) with positive, negative, or mixed values and allows for the user to specify the desired step size: import mathĬomputes domain with given step encompassing series params import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt sns.scatterplot(datadf, ydf'ytarget', xdf'xvariable', hue'cat') I get this. For example, ax.t_major_formatter(ticker.FormatStrFormatter('%0.1f')) I would like to make a scatter plot where I can set my yscale and have it look like this. However, if you wish to have more control over the format, you can define your own formatter. The default tick formatter should do a decent job rounding the tick values to a sensible number of significant digits. ![]() start, end = ax.get_xlim()Īx.t_ticks(np.arange(start, end, stepsize)) If you wish to keep those limits, and just change the stepsize of the tick marks, then you could use ax.get_xlim() to discover what limits Matplotlib has already set. The plt.plot (or ax.plot) function will automatically set default x and y limits. ( np.arange was used rather than Python's range function just in case min(x) and max(x) are floats instead of ints.) Print(g) # -> AxesSubplot(0.672059,0.11 0.227941x0.You could explicitly set where you want to tick marks with plt.xticks: plt.xticks(np.arange(min(x), max(x)+1, 1.0)) # y-axis need to start at zero and end at one # y-axis needs to start at zero and end at 10 ![]() I don't get any errors, but the solution also does not work for me.įig, axes = plt.subplots(nrows=1, ncols=3, figsize=(24, 6))ĭf.groupby(, as_index=False).sum() I tried the solution mentioned here from the Seaborn author. However, for comparison purposes I want the y-axis in all graphs starting at zero and the ending at a specific value. The plot has three graphs in the same figure fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(24, 6)). I'm plotting a CSV file from my simulation results.
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