""" Tests that the file header is properly handled or inferred during parsing for all of the parsers defined in parsers.py """ from collections import namedtuple from io import StringIO import numpy as np import pytest from pandas.errors import ParserError from pandas import DataFrame, Index, MultiIndex import pandas._testing as tm def test_read_with_bad_header(all_parsers): parser = all_parsers msg = r"but only \d+ lines in file" with pytest.raises(ValueError, match=msg): s = StringIO(",,") parser.read_csv(s, header=[10]) def test_negative_header(all_parsers): # see gh-27779 parser = all_parsers data = """1,2,3,4,5 6,7,8,9,10 11,12,13,14,15 """ with pytest.raises( ValueError, match="Passing negative integer to header is invalid. " "For no header, use header=None instead", ): parser.read_csv(StringIO(data), header=-1) @pytest.mark.parametrize("header", [([-1, 2, 4]), ([-5, 0])]) def test_negative_multi_index_header(all_parsers, header): # see gh-27779 parser = all_parsers data = """1,2,3,4,5 6,7,8,9,10 11,12,13,14,15 """ with pytest.raises( ValueError, match="cannot specify multi-index header with negative integers" ): parser.read_csv(StringIO(data), header=header) @pytest.mark.parametrize("header", [True, False]) def test_bool_header_arg(all_parsers, header): # see gh-6114 parser = all_parsers data = """\ MyColumn a b a b""" msg = "Passing a bool to header is invalid" with pytest.raises(TypeError, match=msg): parser.read_csv(StringIO(data), header=header) def test_no_header_prefix(all_parsers): parser = all_parsers data = """1,2,3,4,5 6,7,8,9,10 11,12,13,14,15 """ result = parser.read_csv(StringIO(data), prefix="Field", header=None) expected = DataFrame( [[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14, 15]], columns=["Field0", "Field1", "Field2", "Field3", "Field4"], ) tm.assert_frame_equal(result, expected) def test_header_with_index_col(all_parsers): parser = all_parsers data = """foo,1,2,3 bar,4,5,6 baz,7,8,9 """ names = ["A", "B", "C"] result = parser.read_csv(StringIO(data), names=names) expected = DataFrame( [[1, 2, 3], [4, 5, 6], [7, 8, 9]], index=["foo", "bar", "baz"], columns=["A", "B", "C"], ) tm.assert_frame_equal(result, expected) def test_header_not_first_line(all_parsers): parser = all_parsers data = """got,to,ignore,this,line got,to,ignore,this,line index,A,B,C,D foo,2,3,4,5 bar,7,8,9,10 baz,12,13,14,15 """ data2 = """index,A,B,C,D foo,2,3,4,5 bar,7,8,9,10 baz,12,13,14,15 """ result = parser.read_csv(StringIO(data), header=2, index_col=0) expected = parser.read_csv(StringIO(data2), header=0, index_col=0) tm.assert_frame_equal(result, expected) def test_header_multi_index(all_parsers): parser = all_parsers expected = tm.makeCustomDataframe(5, 3, r_idx_nlevels=2, c_idx_nlevels=4) data = """\ C0,,C_l0_g0,C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g3,R_l1_g3,R3C0,R3C1,R3C2 R_l0_g4,R_l1_g4,R4C0,R4C1,R4C2 """ result = parser.read_csv(StringIO(data), header=[0, 1, 2, 3], index_col=[0, 1]) tm.assert_frame_equal(result, expected) @pytest.mark.parametrize( "kwargs,msg", [ ( dict(index_col=["foo", "bar"]), ( "index_col must only contain " "row numbers when specifying " "a multi-index header" ), ), ( dict(index_col=[0, 1], names=["foo", "bar"]), ("cannot specify names when specifying a multi-index header"), ), ( dict(index_col=[0, 1], usecols=["foo", "bar"]), ("cannot specify usecols when specifying a multi-index header"), ), ], ) def test_header_multi_index_invalid(all_parsers, kwargs, msg): data = """\ C0,,C_l0_g0,C_l0_g1,C_l0_g2 C1,,C_l1_g0,C_l1_g1,C_l1_g2 C2,,C_l2_g0,C_l2_g1,C_l2_g2 C3,,C_l3_g0,C_l3_g1,C_l3_g2 R0,R1,,, R_l0_g0,R_l1_g0,R0C0,R0C1,R0C2 R_l0_g1,R_l1_g1,R1C0,R1C1,R1C2 R_l0_g2,R_l1_g2,R2C0,R2C1,R2C2 R_l0_g3,R_l1_g3,R3C0,R3C1,R3C2 R_l0_g4,R_l1_g4,R4C0,R4C1,R4C2 """ parser = all_parsers with pytest.raises(ValueError, match=msg): parser.read_csv(StringIO(data), header=[0, 1, 2, 3], **kwargs) _TestTuple = namedtuple("names", ["first", "second"]) @pytest.mark.parametrize( "kwargs", [ dict(header=[0, 1]), dict( skiprows=3, names=[ ("a", "q"), ("a", "r"), ("a", "s"), ("b", "t"), ("c", "u"), ("c", "v"), ], ), dict( skiprows=3, names=[ _TestTuple("a", "q"), _TestTuple("a", "r"), _TestTuple("a", "s"), _TestTuple("b", "t"), _TestTuple("c", "u"), _TestTuple("c", "v"), ], ), ], ) def test_header_multi_index_common_format1(all_parsers, kwargs): parser = all_parsers expected = DataFrame( [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]], index=["one", "two"], columns=MultiIndex.from_tuples( [("a", "q"), ("a", "r"), ("a", "s"), ("b", "t"), ("c", "u"), ("c", "v")] ), ) data = """,a,a,a,b,c,c ,q,r,s,t,u,v ,,,,,, one,1,2,3,4,5,6 two,7,8,9,10,11,12""" result = parser.read_csv(StringIO(data), index_col=0, **kwargs) tm.assert_frame_equal(result, expected) @pytest.mark.parametrize( "kwargs", [ dict(header=[0, 1]), dict( skiprows=2, names=[ ("a", "q"), ("a", "r"), ("a", "s"), ("b", "t"), ("c", "u"), ("c", "v"), ], ), dict( skiprows=2, names=[ _TestTuple("a", "q"), _TestTuple("a", "r"), _TestTuple("a", "s"), _TestTuple("b", "t"), _TestTuple("c", "u"), _TestTuple("c", "v"), ], ), ], ) def test_header_multi_index_common_format2(all_parsers, kwargs): parser = all_parsers expected = DataFrame( [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]], index=["one", "two"], columns=MultiIndex.from_tuples( [("a", "q"), ("a", "r"), ("a", "s"), ("b", "t"), ("c", "u"), ("c", "v")] ), ) data = """,a,a,a,b,c,c ,q,r,s,t,u,v one,1,2,3,4,5,6 two,7,8,9,10,11,12""" result = parser.read_csv(StringIO(data), index_col=0, **kwargs) tm.assert_frame_equal(result, expected) @pytest.mark.parametrize( "kwargs", [ dict(header=[0, 1]), dict( skiprows=2, names=[ ("a", "q"), ("a", "r"), ("a", "s"), ("b", "t"), ("c", "u"), ("c", "v"), ], ), dict( skiprows=2, names=[ _TestTuple("a", "q"), _TestTuple("a", "r"), _TestTuple("a", "s"), _TestTuple("b", "t"), _TestTuple("c", "u"), _TestTuple("c", "v"), ], ), ], ) def test_header_multi_index_common_format3(all_parsers, kwargs): parser = all_parsers expected = DataFrame( [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]], index=["one", "two"], columns=MultiIndex.from_tuples( [("a", "q"), ("a", "r"), ("a", "s"), ("b", "t"), ("c", "u"), ("c", "v")] ), ) expected = expected.reset_index(drop=True) data = """a,a,a,b,c,c q,r,s,t,u,v 1,2,3,4,5,6 7,8,9,10,11,12""" result = parser.read_csv(StringIO(data), index_col=None, **kwargs) tm.assert_frame_equal(result, expected) def test_header_multi_index_common_format_malformed1(all_parsers): parser = all_parsers expected = DataFrame( np.array([[2, 3, 4, 5, 6], [8, 9, 10, 11, 12]], dtype="int64"), index=Index([1, 7]), columns=MultiIndex( levels=[["a", "b", "c"], ["r", "s", "t", "u", "v"]], codes=[[0, 0, 1, 2, 2], [0, 1, 2, 3, 4]], names=["a", "q"], ), ) data = """a,a,a,b,c,c q,r,s,t,u,v 1,2,3,4,5,6 7,8,9,10,11,12""" result = parser.read_csv(StringIO(data), header=[0, 1], index_col=0) tm.assert_frame_equal(expected, result) def test_header_multi_index_common_format_malformed2(all_parsers): parser = all_parsers expected = DataFrame( np.array([[2, 3, 4, 5, 6], [8, 9, 10, 11, 12]], dtype="int64"), index=Index([1, 7]), columns=MultiIndex( levels=[["a", "b", "c"], ["r", "s", "t", "u", "v"]], codes=[[0, 0, 1, 2, 2], [0, 1, 2, 3, 4]], names=[None, "q"], ), ) data = """,a,a,b,c,c q,r,s,t,u,v 1,2,3,4,5,6 7,8,9,10,11,12""" result = parser.read_csv(StringIO(data), header=[0, 1], index_col=0) tm.assert_frame_equal(expected, result) def test_header_multi_index_common_format_malformed3(all_parsers): parser = all_parsers expected = DataFrame( np.array([[3, 4, 5, 6], [9, 10, 11, 12]], dtype="int64"), index=MultiIndex(levels=[[1, 7], [2, 8]], codes=[[0, 1], [0, 1]]), columns=MultiIndex( levels=[["a", "b", "c"], ["s", "t", "u", "v"]], codes=[[0, 1, 2, 2], [0, 1, 2, 3]], names=[None, "q"], ), ) data = """,a,a,b,c,c q,r,s,t,u,v 1,2,3,4,5,6 7,8,9,10,11,12""" result = parser.read_csv(StringIO(data), header=[0, 1], index_col=[0, 1]) tm.assert_frame_equal(expected, result) @pytest.mark.parametrize( "data,header", [("1,2,3\n4,5,6", None), ("foo,bar,baz\n1,2,3\n4,5,6", 0)] ) def test_header_names_backward_compat(all_parsers, data, header): # see gh-2539 parser = all_parsers expected = parser.read_csv(StringIO("1,2,3\n4,5,6"), names=["a", "b", "c"]) result = parser.read_csv(StringIO(data), names=["a", "b", "c"], header=header) tm.assert_frame_equal(result, expected) @pytest.mark.parametrize("kwargs", [dict(), dict(index_col=False)]) def test_read_only_header_no_rows(all_parsers, kwargs): # See gh-7773 parser = all_parsers expected = DataFrame(columns=["a", "b", "c"]) result = parser.read_csv(StringIO("a,b,c"), **kwargs) tm.assert_frame_equal(result, expected) @pytest.mark.parametrize( "kwargs,names", [ (dict(), [0, 1, 2, 3, 4]), (dict(prefix="X"), ["X0", "X1", "X2", "X3", "X4"]), ( dict(names=["foo", "bar", "baz", "quux", "panda"]), ["foo", "bar", "baz", "quux", "panda"], ), ], ) def test_no_header(all_parsers, kwargs, names): parser = all_parsers data = """1,2,3,4,5 6,7,8,9,10 11,12,13,14,15 """ expected = DataFrame( [[1, 2, 3, 4, 5], [6, 7, 8, 9, 10], [11, 12, 13, 14, 15]], columns=names ) result = parser.read_csv(StringIO(data), header=None, **kwargs) tm.assert_frame_equal(result, expected) @pytest.mark.parametrize("header", [["a", "b"], "string_header"]) def test_non_int_header(all_parsers, header): # see gh-16338 msg = "header must be integer or list of integers" data = """1,2\n3,4""" parser = all_parsers with pytest.raises(ValueError, match=msg): parser.read_csv(StringIO(data), header=header) def test_singleton_header(all_parsers): # see gh-7757 data = """a,b,c\n0,1,2\n1,2,3""" parser = all_parsers expected = DataFrame({"a": [0, 1], "b": [1, 2], "c": [2, 3]}) result = parser.read_csv(StringIO(data), header=[0]) tm.assert_frame_equal(result, expected) @pytest.mark.parametrize( "data,expected", [ ( "A,A,A,B\none,one,one,two\n0,40,34,0.1", DataFrame( [[0, 40, 34, 0.1]], columns=MultiIndex.from_tuples( [("A", "one"), ("A", "one.1"), ("A", "one.2"), ("B", "two")] ), ), ), ( "A,A,A,B\none,one,one.1,two\n0,40,34,0.1", DataFrame( [[0, 40, 34, 0.1]], columns=MultiIndex.from_tuples( [("A", "one"), ("A", "one.1"), ("A", "one.1.1"), ("B", "two")] ), ), ), ( "A,A,A,B,B\none,one,one.1,two,two\n0,40,34,0.1,0.1", DataFrame( [[0, 40, 34, 0.1, 0.1]], columns=MultiIndex.from_tuples( [ ("A", "one"), ("A", "one.1"), ("A", "one.1.1"), ("B", "two"), ("B", "two.1"), ] ), ), ), ], ) def test_mangles_multi_index(all_parsers, data, expected): # see gh-18062 parser = all_parsers result = parser.read_csv(StringIO(data), header=[0, 1]) tm.assert_frame_equal(result, expected) @pytest.mark.parametrize("index_col", [None, [0]]) @pytest.mark.parametrize( "columns", [None, (["", "Unnamed"]), (["Unnamed", ""]), (["Unnamed", "NotUnnamed"])] ) def test_multi_index_unnamed(all_parsers, index_col, columns): # see gh-23687 # # When specifying a multi-index header, make sure that # we don't error just because one of the rows in our header # has ALL column names containing the string "Unnamed". The # correct condition to check is whether the row contains # ALL columns that did not have names (and instead were given # placeholder ones). parser = all_parsers header = [0, 1] if index_col is None: data = ",".join(columns or ["", ""]) + "\n0,1\n2,3\n4,5\n" else: data = ",".join([""] + (columns or ["", ""])) + "\n,0,1\n0,2,3\n1,4,5\n" if columns is None: msg = ( r"Passed header=\[0,1\] are too " r"many rows for this multi_index of columns" ) with pytest.raises(ParserError, match=msg): parser.read_csv(StringIO(data), header=header, index_col=index_col) else: result = parser.read_csv(StringIO(data), header=header, index_col=index_col) exp_columns = [] for i, col in enumerate(columns): if not col: # Unnamed. col = f"Unnamed: {i if index_col is None else i + 1}_level_0" exp_columns.append(col) columns = MultiIndex.from_tuples(zip(exp_columns, ["0", "1"])) expected = DataFrame([[2, 3], [4, 5]], columns=columns) tm.assert_frame_equal(result, expected) def test_read_csv_multiindex_columns(all_parsers): # GH#6051 parser = all_parsers s1 = "Male, Male, Male, Female, Female\nR, R, L, R, R\n.86, .67, .88, .78, .81" s2 = ( "Male, Male, Male, Female, Female\n" "R, R, L, R, R\n" ".86, .67, .88, .78, .81\n" ".86, .67, .88, .78, .82" ) mi = MultiIndex.from_tuples( [ ("Male", "R"), (" Male", " R"), (" Male", " L"), (" Female", " R"), (" Female", " R.1"), ] ) expected = DataFrame( [[0.86, 0.67, 0.88, 0.78, 0.81], [0.86, 0.67, 0.88, 0.78, 0.82]], columns=mi ) df1 = parser.read_csv(StringIO(s1), header=[0, 1]) tm.assert_frame_equal(df1, expected.iloc[:1]) df2 = parser.read_csv(StringIO(s2), header=[0, 1]) tm.assert_frame_equal(df2, expected)