from datetime import datetime
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from io import StringIO
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from textwrap import dedent
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import numpy as np
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import pytest
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import pandas.util._test_decorators as td
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from pandas import (
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DataFrame,
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Series,
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option_context,
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to_datetime,
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)
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def test_repr_embedded_ndarray():
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arr = np.empty(10, dtype=[("err", object)])
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for i in range(len(arr)):
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arr["err"][i] = np.random.randn(i)
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df = DataFrame(arr)
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repr(df["err"])
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repr(df)
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df.to_string()
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def test_repr_tuples():
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buf = StringIO()
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df = DataFrame({"tups": list(zip(range(10), range(10)))})
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repr(df)
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df.to_string(col_space=10, buf=buf)
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def test_to_string_truncate():
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# GH 9784 - dont truncate when calling DataFrame.to_string
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df = DataFrame(
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[
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{
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"a": "foo",
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"b": "bar",
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"c": "let's make this a very VERY long line that is longer "
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"than the default 50 character limit",
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"d": 1,
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},
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{"a": "foo", "b": "bar", "c": "stuff", "d": 1},
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]
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)
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df.set_index(["a", "b", "c"])
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assert df.to_string() == (
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" a b "
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" c d\n"
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"0 foo bar let's make this a very VERY long line t"
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"hat is longer than the default 50 character limit 1\n"
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"1 foo bar "
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" stuff 1"
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)
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with option_context("max_colwidth", 20):
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# the display option has no effect on the to_string method
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assert df.to_string() == (
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" a b "
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" c d\n"
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"0 foo bar let's make this a very VERY long line t"
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"hat is longer than the default 50 character limit 1\n"
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"1 foo bar "
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" stuff 1"
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)
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assert df.to_string(max_colwidth=20) == (
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" a b c d\n"
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"0 foo bar let's make this ... 1\n"
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"1 foo bar stuff 1"
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)
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@pytest.mark.parametrize(
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"input_array, expected",
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[
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("a", "a"),
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(["a", "b"], "a\nb"),
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([1, "a"], "1\na"),
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(1, "1"),
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([0, -1], " 0\n-1"),
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(1.0, "1.0"),
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([" a", " b"], " a\n b"),
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([".1", "1"], ".1\n 1"),
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(["10", "-10"], " 10\n-10"),
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],
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)
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def test_format_remove_leading_space_series(input_array, expected):
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# GH: 24980
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s = Series(input_array).to_string(index=False)
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assert s == expected
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@pytest.mark.parametrize(
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"input_array, expected",
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[
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({"A": ["a"]}, "A\na"),
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({"A": ["a", "b"], "B": ["c", "dd"]}, "A B\na c\nb dd"),
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({"A": ["a", 1], "B": ["aa", 1]}, "A B\na aa\n1 1"),
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],
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)
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def test_format_remove_leading_space_dataframe(input_array, expected):
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# GH: 24980
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df = DataFrame(input_array).to_string(index=False)
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assert df == expected
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@pytest.mark.parametrize(
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"max_cols, max_rows, expected",
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[
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(
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10,
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None,
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" 0 1 2 3 4 ... 6 7 8 9 10\n"
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" 0 0 0 0 0 ... 0 0 0 0 0\n"
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" 0 0 0 0 0 ... 0 0 0 0 0\n"
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" 0 0 0 0 0 ... 0 0 0 0 0\n"
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" 0 0 0 0 0 ... 0 0 0 0 0",
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),
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(
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None,
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2,
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" 0 1 2 3 4 5 6 7 8 9 10\n"
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" 0 0 0 0 0 0 0 0 0 0 0\n"
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" .. .. .. .. .. .. .. .. .. .. ..\n"
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" 0 0 0 0 0 0 0 0 0 0 0",
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),
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(
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10,
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2,
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" 0 1 2 3 4 ... 6 7 8 9 10\n"
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" 0 0 0 0 0 ... 0 0 0 0 0\n"
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" .. .. .. .. .. ... .. .. .. .. ..\n"
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" 0 0 0 0 0 ... 0 0 0 0 0",
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),
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(
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9,
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2,
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" 0 1 2 3 ... 7 8 9 10\n"
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" 0 0 0 0 ... 0 0 0 0\n"
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" .. .. .. .. ... .. .. .. ..\n"
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" 0 0 0 0 ... 0 0 0 0",
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),
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(
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1,
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1,
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" 0 ...\n 0 ...\n.. ...",
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),
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],
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)
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def test_truncation_no_index(max_cols, max_rows, expected):
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df = DataFrame([[0] * 11] * 4)
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assert df.to_string(index=False, max_cols=max_cols, max_rows=max_rows) == expected
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def test_to_string_unicode_columns(float_frame):
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df = DataFrame({"\u03c3": np.arange(10.0)})
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buf = StringIO()
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df.to_string(buf=buf)
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buf.getvalue()
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buf = StringIO()
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df.info(buf=buf)
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buf.getvalue()
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result = float_frame.to_string()
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assert isinstance(result, str)
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def test_to_string_utf8_columns():
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n = "\u05d0".encode()
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with option_context("display.max_rows", 1):
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df = DataFrame([1, 2], columns=[n])
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repr(df)
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def test_to_string_unicode_two():
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dm = DataFrame({"c/\u03c3": []})
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buf = StringIO()
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dm.to_string(buf)
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def test_to_string_unicode_three():
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dm = DataFrame(["\xc2"])
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buf = StringIO()
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dm.to_string(buf)
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def test_to_string_with_formatters():
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df = DataFrame(
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{
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"int": [1, 2, 3],
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"float": [1.0, 2.0, 3.0],
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"object": [(1, 2), True, False],
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},
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columns=["int", "float", "object"],
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)
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formatters = [
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("int", lambda x: f"0x{x:x}"),
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("float", lambda x: f"[{x: 4.1f}]"),
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("object", lambda x: f"-{x!s}-"),
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]
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result = df.to_string(formatters=dict(formatters))
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result2 = df.to_string(formatters=list(zip(*formatters))[1])
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assert result == (
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" int float object\n"
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"0 0x1 [ 1.0] -(1, 2)-\n"
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"1 0x2 [ 2.0] -True-\n"
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"2 0x3 [ 3.0] -False-"
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)
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assert result == result2
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def test_to_string_with_datetime64_monthformatter():
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months = [datetime(2016, 1, 1), datetime(2016, 2, 2)]
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x = DataFrame({"months": months})
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def format_func(x):
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return x.strftime("%Y-%m")
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result = x.to_string(formatters={"months": format_func})
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expected = dedent(
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"""\
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months
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0 2016-01
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1 2016-02"""
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)
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assert result.strip() == expected
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def test_to_string_with_datetime64_hourformatter():
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x = DataFrame(
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{"hod": to_datetime(["10:10:10.100", "12:12:12.120"], format="%H:%M:%S.%f")}
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)
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def format_func(x):
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return x.strftime("%H:%M")
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result = x.to_string(formatters={"hod": format_func})
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expected = dedent(
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"""\
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hod
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0 10:10
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1 12:12"""
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)
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assert result.strip() == expected
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def test_to_string_with_formatters_unicode():
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df = DataFrame({"c/\u03c3": [1, 2, 3]})
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result = df.to_string(formatters={"c/\u03c3": str})
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expected = dedent(
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"""\
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c/\u03c3
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0 1
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1 2
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2 3"""
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)
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assert result == expected
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def test_to_string_complex_number_trims_zeros():
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s = Series([1.000000 + 1.000000j, 1.0 + 1.0j, 1.05 + 1.0j])
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result = s.to_string()
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expected = dedent(
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"""\
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0 1.00+1.00j
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1 1.00+1.00j
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2 1.05+1.00j"""
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)
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assert result == expected
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def test_nullable_float_to_string(float_ea_dtype):
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# https://github.com/pandas-dev/pandas/issues/36775
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dtype = float_ea_dtype
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s = Series([0.0, 1.0, None], dtype=dtype)
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result = s.to_string()
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expected = dedent(
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"""\
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0 0.0
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1 1.0
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2 <NA>"""
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)
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assert result == expected
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def test_nullable_int_to_string(any_int_ea_dtype):
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# https://github.com/pandas-dev/pandas/issues/36775
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dtype = any_int_ea_dtype
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s = Series([0, 1, None], dtype=dtype)
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result = s.to_string()
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expected = dedent(
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"""\
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0 0
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1 1
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2 <NA>"""
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)
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assert result == expected
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@pytest.mark.parametrize("na_rep", ["NaN", "Ted"])
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def test_to_string_na_rep_and_float_format(na_rep):
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# GH 13828
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df = DataFrame([["A", 1.2225], ["A", None]], columns=["Group", "Data"])
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result = df.to_string(na_rep=na_rep, float_format="{:.2f}".format)
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expected = dedent(
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f"""\
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Group Data
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0 A 1.22
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1 A {na_rep}"""
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)
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assert result == expected
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@pytest.mark.parametrize(
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"data,expected",
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[
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(
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{"col1": [1, 2], "col2": [3, 4]},
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" col1 col2\n0 1 3\n1 2 4",
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),
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(
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{"col1": ["Abc", 0.756], "col2": [np.nan, 4.5435]},
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" col1 col2\n0 Abc NaN\n1 0.756 4.5435",
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),
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(
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{"col1": [np.nan, "a"], "col2": [0.009, 3.543], "col3": ["Abc", 23]},
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" col1 col2 col3\n0 NaN 0.009 Abc\n1 a 3.543 23",
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),
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],
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)
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def test_to_string_max_rows_zero(data, expected):
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# GH35394
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result = DataFrame(data=data).to_string(max_rows=0)
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assert result == expected
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@td.skip_if_no("pyarrow")
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def test_to_string_string_dtype():
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# GH#50099
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df = DataFrame({"x": ["foo", "bar", "baz"], "y": ["a", "b", "c"], "z": [1, 2, 3]})
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df = df.astype(
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{"x": "string[pyarrow]", "y": "string[python]", "z": "int64[pyarrow]"}
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)
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result = df.dtypes.to_string()
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expected = dedent(
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"""\
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x string[pyarrow]
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y string[python]
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z int64[pyarrow]"""
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)
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assert result == expected
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