code: def expected_results():
      return {
          "id": {
              "25%": check_is_NaN,
              "5%": check_is_NaN,
              "50%": check_is_NaN,
              "75%": check_is_NaN,
              "95%": check_is_NaN,
              "count": 9,
              "cv": check_is_NaN,
              "n_distinct": 8,
              "histogram": check_is_NaN,
              "iqr": check_is_NaN,
              "is_unique": False,
              "kurtosis": check_is_NaN,
              "mad": check_is_NaN,
              "max": check_is_NaN,
              "mean": check_is_NaN,
              "min": check_is_NaN,
              "mini_histogram": check_is_NaN,
              "n_missing": 0,
              "p_missing": 0.0,
              "p_distinct": 0.88888888,
              "p_zeros": check_is_NaN,
              "range": check_is_NaN,
              "skewness": check_is_NaN,
              "std": check_is_NaN,
              "sum": check_is_NaN,
              "variance": check_is_NaN,
          },
          "x": {
              "25%": -0.75,
              "5%": -7.5499999999999989,
              "50%": 2.5,
              "75%": 23.75,
              "95%": 50.0,
              "count": 8,
              "n_infinite": 0,
              "p_infinite": 0,
              "cv": 1.771071190261633,
              "n_distinct": 6,
              "iqr": 24.5,
              "is_unique": False,
              "kurtosis": -0.50292858929003803,
              "mad": 9.0,
              "max": 50.0,
              "mean": 13.375,
              "min": -10.0,
              "n_missing": 1,
              "p_missing": 0.11111111111111116,
              "n_negative": 2,
              "p_negative": 0.22222222222222222,
              "p_distinct": 6 / 8,
              "n": 9,
              "n_zeros": 2,
              "p_zeros": 0.2222222222222222,
              "range": 60.0,
              "skewness": 1.0851622393567653,
              "std": 23.688077169749342,
              "sum": 107.0,
              "variance": 561.125,
          },
          "y": {
              "25%": 10.125000249999999,
              "5%": -2.0420348747749997,
              "50%": 15.942256,
              "75%": 246.78800000000001,
              "95%": 2258.2531999999987,
              "count": 8,
              "n_infinite": 0,
              "p_infinite": 0,
              "cv": 2.2112992878833846,
              "n_distinct": 8,
              "iqr": 236.66299975000001,
              "is_unique": True,
              "kurtosis": 6.974137018717359,
              "mad": 17.51305182675,
              "max": 3122.0,
              "mean": 491.17436504331249,
              "min": -3.1415926535000001,
              "n_missing": 1,
              "p_missing": 0.11111111111111116,
              "n_negative": 1,
              "p_negative": 0.11111111111111116,
              "p_distinct": 1,
              "n_zeros": 0,
              "p_zeros": 0.0,
              "range": 3125.1415926535001,
              "skewness": 2.6156591135729266,
              "std": 1086.1335236468506,
              "sum": 3929.3949203464999,
              "variance": 1179686.0311895239,
          },
          "cat": {
              "25%": check_is_NaN,
              "5%": check_is_NaN,
              "50%": check_is_NaN,
              "75%": check_is_NaN,
              "95%": check_is_NaN,
              "count": 8,
              "cv": check_is_NaN,
              "n_distinct": 6,
              "histogram": check_is_NaN,
              "iqr": check_is_NaN,
              "is_unique": False,
              "kurtosis": check_is_NaN,
              "mad": check_is_NaN,
              "max": check_is_NaN,
              "mean": check_is_NaN,
              "min": check_is_NaN,
              "mini_histogram": check_is_NaN,
              "n_missing": 1,
              "p_missing": 0.11111111111111116,
              "p_distinct": 6 / 8,
              "p_zeros": check_is_NaN,
              "range": check_is_NaN,
              "skewness": check_is_NaN,
              "std": check_is_NaN,
              "sum": check_is_NaN,
              "variance": check_is_NaN,
          },
          "s1": {
              "25%": 1.0,
              "5%": 1.0,
              "50%": 1.0,
              "75%": 1.0,
              "95%": 1.0,
              "count": 9,
              "cv": 0,
              "iqr": 0,
              "is_unique": False,
              "kurtosis": 0,
              "mad": 0.0,
              "max": 1.0,
              "mean": 1.0,
              "min": 1.0,
              "n_missing": 0,
              "p_missing": 0.0,
              "n_negative": 0,
              "p_negative": 0.0,
              "n_infinite": 0,
              "n_distinct": 1,
              "p_distinct": 0.1111111111111111,
              "p_zeros": 0,
              "range": 0,
              "skewness": 0,
              "std": 0,
              "sum": 9,
              "variance": 0.0,
              "monotonic_increase": True,
              "monotonic_increase_strict": False,
          },
          "s2": {
              "25%": check_is_NaN,
              "5%": check_is_NaN,
              "50%": check_is_NaN,
              "75%": check_is_NaN,
              "95%": check_is_NaN,
              "count": 9,
              "cv": check_is_NaN,
              "n_distinct": 1,
              "histogram": check_is_NaN,
              "iqr": check_is_NaN,
              "is_unique": False,
              "kurtosis": check_is_NaN,
              "mad": check_is_NaN,
              "max": check_is_NaN,
              "mean": check_is_NaN,
              "min": check_is_NaN,
              "mini_histogram": check_is_NaN,
              "n_missing": 0,
              "p_missing": 0.0,
              "p_distinct": 0.1111111111111111,
              "p_zeros": check_is_NaN,
              "range": check_is_NaN,
              "skewness": check_is_NaN,
              "std": check_is_NaN,
              "sum": check_is_NaN,
              "variance": check_is_NaN,
          },
          "somedate": {
              "25%": check_is_NaN,
              "5%": check_is_NaN,
              "50%": check_is_NaN,
              "75%": check_is_NaN,
              "95%": check_is_NaN,
              "count": 8,
              "cv": check_is_NaN,
              "n_distinct": 5,
              "iqr": check_is_NaN,
              "is_unique": False,
              "kurtosis": check_is_NaN,
              "mad": check_is_NaN,
              "max": datetime.datetime(2022, 1, 1, 13, 57),
              "mean": check_is_NaN,
              "min": datetime.datetime(1898, 1, 2),
              "n_missing": 1,
              "p_missing": 0.11111111111111116,
              "p_distinct": 5 / 8,
              "p_zeros": check_is_NaN,
              "range": datetime.timedelta(45289, hours=13, minutes=57),
              "skewness": check_is_NaN,
              "std": check_is_NaN,
              "sum": check_is_NaN,
          },
          "bool_tf": {
              "25%": check_is_NaN,
              "5%": check_is_NaN,
              "50%": check_is_NaN,
              "75%": check_is_NaN,
              "95%": check_is_NaN,
              "count": 9,
              "cv": check_is_NaN,
              "n_distinct": 2,
              "histogram": check_is_NaN,
              "iqr": check_is_NaN,
              "is_unique": False,
              "kurtosis": check_is_NaN,
              "mad": check_is_NaN,
              "max": check_is_NaN,
              "min": check_is_NaN,
              "mini_histogram": check_is_NaN,
              "n_missing": 0,
              "p_missing": 0,
              "p_distinct": 2 / 9,
              "p_zeros": check_is_NaN,
              "range": check_is_NaN,
              "skewness": check_is_NaN,
              "std": check_is_NaN,
              "sum": check_is_NaN,
              "variance": check_is_NaN,
          },
          "bool_tf_with_nan": {
              "25%": check_is_NaN,
              "5%": check_is_NaN,
              "50%": check_is_NaN,
              "75%": check_is_NaN,
              "95%": check_is_NaN,
              "n": 9,
              "count": 8,
              "cv": check_is_NaN,
              "n_distinct": 2,
              "p_distinct": 2 / 8,
              "n_missing": 1,
              "p_missing": 1 / 9,
              "histogram": check_is_NaN,
              "iqr": check_is_NaN,
              "is_unique": False,
              "kurtosis": check_is_NaN,
              "mad": check_is_NaN,
              "max": check_is_NaN,
              "min": check_is_NaN,
              "mini_histogram": check_is_NaN,
              "p_zeros": check_is_NaN,
              "range": check_is_NaN,
              "skewness": check_is_NaN,
              "std": check_is_NaN,
              "sum": check_is_NaN,
              "variance": check_is_NaN,
          },
          "bool_01": {
              "5%": 0,
              "25%": 0,
              "50%": 1.0,
              "75%": 1,
              "95%": 1,
              "n": 9,
              "count": 9,
              "cv": 0.9486832980505138,
              "n_distinct": 2,
              "iqr": 1.0,
              "is_unique": False,
              "mad": 0,
              "max": 1,
              "min": 0,
              "n_missing": 0,
              "p_missing": 0,
              "p_distinct": 2 / 9,
              "p_zeros": 4 / 9,
              "sum": 5,
          },
          "bool_01_with_nan": {
              "5%": 0,
              "25%": 0,
              "50%": 0.5,
              "75%": 1,
              "95%": 1,
              "n": 9,
              "count": 8,
              "cv": 1.0690449676496976,
              "n_distinct": 2,
              "iqr": 1.0,
              "is_unique": False,
              "kurtosis": -2.8000000000000003,
              "mad": 0.5,
              "max": 1,
              "min": 0,
              "n_missing": 1,
              "p_missing": 0.11111111111111116,
              "p_distinct": 2 / 8,
              "n_zeros": 4,
              "p_zeros": 4 / 9,
              "range": 1.0,
              "skewness": 0.0,
              "std": 0.5345224838248488,
              "sum": 4.0,
              "variance": 0.2857142857142857,
          },
          "list": {
              "n": 9,
              "count": 9,
              "n_missing": 0,
              "p_missing": 0,
          },
          "mixed": {
              "n": 9,
              "count": 9,
              "n_missing": 0,
              "p_missing": 0,
          },
          "dict": {
              "n": 9,
              "count": 9,
              "n_missing": 0,
              "p_missing": 0,
          },
          "tuple": {
              "n": 9,
              "count": 9,
              "n_missing": 0,
              "p_missing": 0,
          },
      }
  
file_path: ydata-profiling/tests/unit/test_describe.py
imports: import datetime
  from dataclasses import asdict
  import numpy
  import pandas
  import pytest
  from ydata_profiling.config import Settings
  from ydata_profiling.model.describe import describe
  from ydata_profiling.model.summary import describe_1d
  from ydata_profiling.model.typeset import ProfilingTypeSet
label_desc: Use image node_id 4 for calling a global function with example usage: expected_results() and returns: dict