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API: better warnings for df.set_index
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| Original file line number | Diff line number | Diff line change |
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| import pytest | ||
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| import numpy as np | ||
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| from pandas import compat | ||
| import pandas.util.testing as tm | ||
| from pandas import DataFrame, date_range, NaT | ||
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| @pytest.fixture | ||
| def float_frame(): | ||
| """ | ||
| Fixture for DataFrame of floats with index of unique strings | ||
| Columns are ['A', 'B', 'C', 'D']. | ||
| """ | ||
| return DataFrame(tm.getSeriesData()) | ||
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| @pytest.fixture | ||
| def float_frame2(): | ||
| """ | ||
| Fixture for DataFrame of floats with index of unique strings | ||
| Columns are ['D', 'C', 'B', 'A'] | ||
| """ | ||
| return DataFrame(tm.getSeriesData(), columns=['D', 'C', 'B', 'A']) | ||
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| @pytest.fixture | ||
| def int_frame(): | ||
| """ | ||
| Fixture for DataFrame of ints with index of unique strings | ||
| Columns are ['A', 'B', 'C', 'D'] | ||
| """ | ||
| df = DataFrame({k: v.astype(int) | ||
| for k, v in compat.iteritems(tm.getSeriesData())}) | ||
| # force these all to int64 to avoid platform testing issues | ||
| return DataFrame({c: s for c, s in compat.iteritems(df)}, dtype=np.int64) | ||
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| @pytest.fixture | ||
| def datetime_frame(): | ||
| """ | ||
| Fixture for DataFrame of floats with DatetimeIndex | ||
| Columns are ['A', 'B', 'C', 'D'] | ||
| """ | ||
| return DataFrame(tm.getTimeSeriesData()) | ||
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| @pytest.fixture | ||
| def float_string_frame(): | ||
| """ | ||
| Fixture for DataFrame of floats and strings with index of unique strings | ||
| Columns are ['A', 'B', 'C', 'D', 'foo']. | ||
| """ | ||
| df = DataFrame(tm.getSeriesData()) | ||
| df['foo'] = 'bar' | ||
| return df | ||
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| @pytest.fixture | ||
| def mixed_float_frame(): | ||
| """ | ||
| Fixture for DataFrame of different float types with index of unique strings | ||
| Columns are ['A', 'B', 'C', 'D']. | ||
| """ | ||
| df = DataFrame(tm.getSeriesData()) | ||
| df.A = df.A.astype('float16') | ||
| df.B = df.B.astype('float32') | ||
| df.C = df.C.astype('float64') | ||
| return df | ||
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| @pytest.fixture | ||
| def mixed_float_frame2(): | ||
| """ | ||
| Fixture for DataFrame of different float types with index of unique strings | ||
| Columns are ['A', 'B', 'C', 'D']. | ||
| """ | ||
| df = DataFrame(tm.getSeriesData()) | ||
| df.D = df.D.astype('float16') | ||
| df.C = df.C.astype('float32') | ||
| df.B = df.B.astype('float64') | ||
| return df | ||
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| @pytest.fixture | ||
| def mixed_int_frame(): | ||
| """ | ||
| Fixture for DataFrame of different int types with index of unique strings | ||
| Columns are ['A', 'B', 'C', 'D']. | ||
| """ | ||
| df = DataFrame({k: v.astype(int) | ||
| for k, v in compat.iteritems(tm.getSeriesData())}) | ||
| df.A = df.A.astype('uint8') | ||
| df.B = df.B.astype('int32') | ||
| df.C = df.C.astype('int64') | ||
| df.D = np.ones(len(df.D), dtype='uint64') | ||
| return df | ||
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| @pytest.fixture | ||
| def mixed_type_frame(): | ||
| """ | ||
| Fixture for DataFrame of float/int/string columns with RangeIndex | ||
| Columns are ['a', 'b', 'c', 'float32', 'int32']. | ||
| """ | ||
| return DataFrame({'a': 1., 'b': 2, 'c': 'foo', | ||
| 'float32': np.array([1.] * 10, dtype='float32'), | ||
| 'int32': np.array([1] * 10, dtype='int32')}, | ||
| index=np.arange(10)) | ||
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| @pytest.fixture | ||
| def timezone_frame(): | ||
| """ | ||
| Fixture for DataFrame of date_range Series with different time zones | ||
| Columns are ['A', 'B', 'C']; some entries are missing | ||
| """ | ||
| df = DataFrame({'A': date_range('20130101', periods=3), | ||
| 'B': date_range('20130101', periods=3, | ||
| tz='US/Eastern'), | ||
| 'C': date_range('20130101', periods=3, | ||
| tz='CET')}) | ||
| df.iloc[1, 1] = NaT | ||
| df.iloc[1, 2] = NaT | ||
| return df | ||
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| @pytest.fixture | ||
| def empty_frame(): | ||
| """ | ||
| Fixture for empty DataFrame | ||
| """ | ||
| return DataFrame({}) | ||
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| @pytest.fixture | ||
| def datetime_series(): | ||
| """ | ||
| Fixture for Series of floats with DatetimeIndex | ||
| """ | ||
| return tm.makeTimeSeries(nper=30) | ||
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| @pytest.fixture | ||
| def datetime_series_short(): | ||
| """ | ||
| Fixture for Series of floats with DatetimeIndex | ||
| """ | ||
| return tm.makeTimeSeries(nper=30)[5:] | ||
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| @pytest.fixture | ||
| def simple_frame(): | ||
| """ | ||
| Fixture for simple 3x3 DataFrame | ||
| Columns are ['one', 'two', 'three'], index is ['a', 'b', 'c']. | ||
| """ | ||
| arr = np.array([[1., 2., 3.], | ||
| [4., 5., 6.], | ||
| [7., 8., 9.]]) | ||
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| return DataFrame(arr, columns=['one', 'two', 'three'], | ||
| index=['a', 'b', 'c']) | ||
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| @pytest.fixture | ||
| def frame_of_index_cols(): | ||
| """ | ||
| Fixture for DataFrame of columns that can be used for indexing | ||
| Columns are ['A', 'B', 'C', 'D', 'E']; 'A' & 'B' contain duplicates (but | ||
| are jointly unique), the rest are unique. | ||
| """ | ||
| df = DataFrame({'A': ['foo', 'foo', 'foo', 'bar', 'bar'], | ||
| 'B': ['one', 'two', 'three', 'one', 'two'], | ||
| 'C': ['a', 'b', 'c', 'd', 'e'], | ||
| 'D': np.random.randn(5), | ||
| 'E': np.random.randn(5)}) | ||
| return df |
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