def test_df_equal(self): fLOG(__file__, self._testMethodName, OutputPrint=__name__ == "__main__") exp1 = pandas.DataFrame( [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)]) exp2 = pandas.DataFrame( [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)]) assert df_equal(exp1, exp2) exp1 = pandas.DataFrame( [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)]) exp2 = pandas.DataFrame( [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)]) exp2 = exp2[["k2", "k1", "v", "i"]] assert df_equal(exp1, exp2) exp1 = pandas.DataFrame( [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)]) exp2 = pandas.DataFrame( [dict(k1="a", k2="b", v=3, i=1), dict(k1="b", k2="b", v=1, i=2)]) assert not df_equal(exp1, exp2) exp1 = pandas.DataFrame( [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)]) exp2 = pandas.DataFrame([ dict(k1="a", k2="b", v=numpy.nan, i=1), dict(k1="b", k2="b", v=1, i=2) ]) assert not df_equal(exp1, exp2) exp1 = pandas.DataFrame([ dict(k1="a", k2="b", v=numpy.nan, i=1), dict(k1="b", k2="b", v=1, i=2) ]) exp2 = pandas.DataFrame([ dict(k1="a", k2="b", v=numpy.nan, i=1), dict(k1="b", k2="b", v=1, i=2) ]) assert not df_equal(exp1, exp2)
def test_groupby_sort_head(self): fLOG( __file__, self._testMethodName, OutputPrint=__name__ == "__main__") l = [dict(k1="a", k2="b", v=4, i=1), dict(k1="a", k2="b", v=5, i=1), dict(k1="a", k2="b", v=4, i=2), dict(k1="b", k2="b", v=1, i=2), dict(k1="b", k2="b", v=1, i=3), ] exp = [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2), ] df = pandas.DataFrame(l) exp = pandas.DataFrame(exp) res = groupby_topn(df, by_keys=["k1", "k2"], sort_keys=["v", "i"], as_index=False) b = df_equal(exp, res) if not b: raise Exception( "dataframe not equal\nRES:\n{0}\nEXP\n{1}".format(str(res), str(exp)))
def test_groupby_sort_head(self): fLOG(__file__, self._testMethodName, OutputPrint=__name__ == "__main__") ld = [ dict(k1="a", k2="b", v=4, i=1), dict(k1="a", k2="b", v=5, i=1), dict(k1="a", k2="b", v=4, i=2), dict(k1="b", k2="b", v=1, i=2), dict(k1="b", k2="b", v=1, i=3) ] exp = [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)] df = pandas.DataFrame(ld) exp = pandas.DataFrame(exp) res = groupby_topn(df, by_keys=["k1", "k2"], sort_keys=["v", "i"], as_index=False) b = df_equal(exp, res) if not b: raise Exception("dataframe not equal\nRES:\n{0}\nEXP\n{1}".format( str(res), str(exp)))
def test_faq_pandas(self): fLOG(__file__, self._testMethodName, OutputPrint=__name__ == "__main__") df = pandas.DataFrame([{"a": 1}]) if False: # does not work df_to_clipboard(df) assert df_equal(df, df) speed_dataframe()
def test_faq_pandas(self): fLOG( __file__, self._testMethodName, OutputPrint=__name__ == "__main__") df = pandas.DataFrame([{"a": 1}]) if False: # does not work df_to_clipboard(df) assert df_equal(df, df) speed_dataframe()
def test_df_equal(self): fLOG( __file__, self._testMethodName, OutputPrint=__name__ == "__main__") exp1 = pandas.DataFrame( [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)]) exp2 = pandas.DataFrame( [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)]) assert df_equal(exp1, exp2) exp1 = pandas.DataFrame( [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)]) exp2 = pandas.DataFrame( [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)]) exp2 = exp2[["k2", "k1", "v", "i"]] assert df_equal(exp1, exp2) exp1 = pandas.DataFrame( [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)]) exp2 = pandas.DataFrame( [dict(k1="a", k2="b", v=3, i=1), dict(k1="b", k2="b", v=1, i=2)]) assert not df_equal(exp1, exp2) exp1 = pandas.DataFrame( [dict(k1="a", k2="b", v=4, i=1), dict(k1="b", k2="b", v=1, i=2)]) exp2 = pandas.DataFrame( [dict(k1="a", k2="b", v=numpy.nan, i=1), dict(k1="b", k2="b", v=1, i=2)]) assert not df_equal(exp1, exp2) exp1 = pandas.DataFrame( [dict(k1="a", k2="b", v=numpy.nan, i=1), dict(k1="b", k2="b", v=1, i=2)]) exp2 = pandas.DataFrame( [dict(k1="a", k2="b", v=numpy.nan, i=1), dict(k1="b", k2="b", v=1, i=2)]) assert not df_equal(exp1, exp2)