René's URL Explorer Experiment

{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"Inconsistent behavior between Normalizers when input is Dataframe","articleBody":"\u003c!--To help us understand and resolve your issue, please fill out the form to the best of your ability.--\u003e\r\n\u003c!--You can feel free to delete the sections that do not apply.--\u003e\r\n\r\n### Bug report\r\n\r\n**Bug summary**\r\nIt seems matplotlib.colors.Normalize can work with pandas.Series inputs, whereas LogNorm can't.\r\n\r\n\u003c!--A short 1-2 sentences that succinctly describes the bug--\u003e\r\n\r\n**Code for reproduction**\r\n\r\n\u003c!--A minimum code snippet required to reproduce the bug.\r\nPlease make sure to minimize the number of dependencies required, and provide\r\nany necessary plotted data.\r\nAvoid using threads, as Matplotlib is (explicitly) not thread-safe.--\u003e\r\n\r\n```python\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nfrom matplotlib.collections import LineCollection\r\nfrom matplotlib.colors import ListedColormap, BoundaryNorm, Normalize, LogNorm\r\nimport pandas as pd\r\n\r\nx = np.linspace(0, 3 * np.pi, 500)\r\ny = np.sin(x)\r\ndydx = np.linspace(0, 3 * np.pi, 500) +1  # first derivative\r\ndf= pd.DataFrame({'x':x,'y':y,'dydx':dydx})\r\npoints = np.array([df['x'], df['y']]).T.reshape(-1, 1, 2)\r\nsegments = np.concatenate([points[:-1], points[1:]], axis=1)\r\nfig, axs = plt.subplots()\r\n\r\n# Create a continuous norm to map from data points to colors\r\nnorm = LogNorm(df['dydx'].min(), df['dydx'].max())\r\nlc = LineCollection(segments, cmap='viridis', norm=norm)\r\n# Set the values used for colormapping\r\nlc.set_array(df['dydx'])\r\nlc.set_linewidth(2)\r\nline = axs.add_collection(lc)\r\nfig.colorbar(line, ax=axs)\r\naxs.set_xlim(x.min(), x.max())\r\naxs.set_ylim(-1.1, 1.1)\r\nplt.show()\r\n```\r\n\r\n**Actual outcome**\r\n\r\n\u003c!--The output produced by the above code, which may be a screenshot, console output, etc.--\u003e\r\n\r\n```\r\nTypeError: '\u003c=' not supported between instances of 'SingleBlockManager' and 'int'\r\n```\r\n\r\n**Expected outcome**\r\n\r\nNot sure about what's expected, but if I do `Normalize` instead of `LogNorm` it works, if I do `lc.set_array(df['dydx'].to_numpy())`  instead of `lc.set_array(df['dydx'])` it also works. It's the combination of LogNorm and pd.Series is the problem.\r\n\r\n\u003c!--A description of the expected outcome from the code snippet--\u003e\r\n\u003c!--If this used to work in an earlier version of Matplotlib, please note the version it used to work on--\u003e\r\n\r\n**Matplotlib version**\r\n\u003c!--Please specify your platform and versions of the relevant libraries you are using:--\u003e\r\nversion 3.1.1\r\nmodule://ipykernel.pylab.backend_inline\r\n\r\n\u003c!--Please tell us how you installed matplotlib and python e.g., from source, pip, conda--\u003e\r\n\u003c!--If you installed from conda, please specify which channel you used if not the default--\u003e\r\n\r\n","author":{"url":"https://github.com/alicanb","@type":"Person","name":"alicanb"},"datePublished":"2020-02-03T20:22:51.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":4},"url":"https://github.com/16400/matplotlib/issues/16400"}