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Even if the\nvalue 1 does not occur in the data, we want an entry for it in the table.\n\n" }, { "__type": "Code", "__tag": 4050, "value": "q1 = [2, 3, 3, 2, 4, 4, 2, 3, 4, 4, 4, 3, 3, 3, 4] # 1 does not occur.\nq2 = [4, 4, 2, 2, 2, 4, 1, 1, 2, 2, 4, 2, 2, 2, 4] # 3 does not occur.\noptions = [1, 2, 3, 4]\nres = crosstab(q1, q2, levels=(options, options))\nres.count\n", "execution_status": "success" }, { "__type": "Text", "__tag": 4046, "value": "\nIf `levels` is given, but an element of `levels` is None, the unique values\nof the corresponding argument are used. For example,\n\n" }, { "__type": "Code", "__tag": 4050, "value": "res = crosstab(q1, q2, levels=(None, options))\nres.elements\nres.count\n", "execution_status": "success" }, { "__type": "Text", "__tag": 4046, "value": "\nIf we want to ignore the pairs where 4 occurs in ``q2``, we can\ngive just the values [1, 2] to `levels`, and the 4 will be ignored:\n\n" }, { "__type": "Code", "__tag": 4050, "value": "res = crosstab(q1, q2, levels=(None, [1, 2]))\nres.elements\nres.count\n", "execution_status": "success" }, { "__type": "Text", "__tag": 4046, "value": "\nFinally, let's repeat the first example, but return a sparse matrix:\n\n" }, { "__type": "Code", "__tag": 4050, "value": "res = crosstab(a, x, sparse=True)\n", "execution_status": "success" }, { "__type": "Code", "__tag": 4050, "value": "res.count\n", "execution_status": "failure" }, { "__type": "Code", "__tag": 4050, "value": "res.count.toarray()\n", "execution_status": "success" } ], "title": [], "level": 0, "target": null }, "see_also": [ { "__type": "SeeAlsoItem", "__tag": 4028, "name": { "__type": "CrossRef", "__tag": 4002, "value": "numpy.unique", "reference": { "__type": "RefInfo", "__tag": 4000, "module": "current-module", "version": "current-version", "kind": "to-resolve", "path": "numpy.unique" }, "kind": "module" }, "descriptions": [], "type": null } ], "signature": { "__type": "SignatureNode", "__tag": 4029, "kind": "function", "parameters": [ { "__type": "SigParam", "__tag": 4030, "name": "args", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "VAR_POSITIONAL", "default": { "__type": "Empty", "__tag": 4031 } }, { "__type": "SigParam", "__tag": 4030, "name": "levels", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "KEYWORD_ONLY", "default": "None" }, { "__type": "SigParam", "__tag": 4030, "name": "sparse", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "KEYWORD_ONLY", "default": "False" } ], "return_annotation": { "__type": "Empty", "__tag": 4031 }, "target_name": "crosstab" }, "references": [ ".. [1] \"Contingency table\", http://en.wikipedia.org/wiki/Contingency_table" ], "qa": "scipy.stats._crosstab:crosstab", "arbitrary": [], "local_refs": [ "*args", "levels", "res", "sparse" ] }