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        "\n# 2D Scatter\n\nScatter data in two dimensions.\n\nThe x-axis and y-axis define the coordinates of the scattered points.\n\n.. code::\n\n  @NX_class = \"NXroot\"\n  @default = \"scan1\"\n  scan1:\n    @NX_class = \"NXentry\"\n    @default = \"data\"\n    data:\n      @NX_class = \"NXdata\"\n      @x_indices = [0]\n      @y_indices = [0]\n      @signal = \"z\"\n      x: NX_FLOAT64[500]\n      y: NX_FLOAT64[500]\n      z: NX_FLOAT64[500]\n\nExplanation:\n\n1. ``@axes`` is omitted since default axes are not applicable.\n\n2. ``z`` is the default signal to be plotted versus ``x`` and ``y``.\n\n3. Each data point in ``z`` has a coordinate in ``x`` and ``y``.\n\nNote that the NXdata structure does **not** describe how the data needs to\nbe plotted. In this example we create a 2D scatter plot in the XY-plane.\nBut the data could also be plotted as a function of ``x`` or ``y`` in a\n`sphx_glr_classes_base_classes_data_plot_curve.py` plot. When defining\n``@axes=\"x\"`` the curve plot would be the most likely intention of the data\npublisher but it is up to the reader to decide how to plot the data.\n"
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      "cell_type": "code",
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      "source": [
        "# Data\nimport numpy as np\n\nrstate = np.random.RandomState(42)\nx = rstate.uniform(-3, 3, 500)\ny = rstate.uniform(-3, 3, 500)\nz = (1 - x / 2 + x**5 + y**3) * np.exp(-(x**2) - y**2)\n\n# Plot\nimport matplotlib.pyplot as plt  # noqa E402\n\nplt.style.use(\"_mpl-gallery-nogrid\")\n\nfig, ax = plt.subplots()\nax.scatter(x, y, c=z, s=50, alpha=0.7)\n\nplt.show()"
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