Example #1
0
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('float32')
    df.C = df.C.astype('float32')
    df.B = df.B.astype('float16')
    df.D = df.D.astype('float64')
    return df
Example #2
0
def mixed_int_frame():
    """
    Fixture for DataFrame of different int types with index of unique strings

    Columns are ['A', 'B', 'C', 'D'].

                A  B    C    D
    mUrCZ67juP  0  1    2    2
    rw99ACYaKS  0  1    0    0
    7QsEcpaaVU  0  1    1    1
    xkrimI2pcE  0  1    0    0
    dz01SuzoS8  0  1  255  255
    ccQkqOHX75 -1  1    0    0
    DN0iXaoDLd  0  1    0    0
    ...        .. ..  ...  ...
    Dfb141wAaQ  1  1  254  254
    IPD8eQOVu5  0  1    0    0
    CcaKulsCmv  0  1    0    0
    rIBa8gu7E5  0  1    0    0
    RP6peZmh5o  0  1    1    1
    NMb9pipQWQ  0  1    0    0
    PqgbJEzjib  0  1    3    3

    [30 rows x 4 columns]
    """
    df = DataFrame({k: v.astype(int) for k, v in tm.getSeriesData().items()})
    df.A = df.A.astype('int32')
    df.B = np.ones(len(df.B), dtype='uint64')
    df.C = df.C.astype('uint8')
    df.D = df.C.astype('int64')
    return df
Example #3
0
def mixed_float_frame():
    """
    Fixture for DataFrame of different float types with index of unique strings

    Columns are ['A', 'B', 'C', 'D'].

                       A         B         C         D
    GI7bbDaEZe -0.237908 -0.246225 -0.468506  0.752993
    KGp9mFepzA -1.140809 -0.644046 -1.225586  0.801588
    VeVYLAb1l2 -1.154013 -1.677615  0.690430 -0.003731
    kmPME4WKhO  0.979578  0.998274 -0.776367  0.897607
    CPyopdXTiz  0.048119 -0.257174  0.836426  0.111266
    0kJZQndAj0  0.274357 -0.281135 -0.344238  0.834541
    tqdwQsaHG8 -0.979716 -0.519897  0.582031  0.144710
    ...              ...       ...       ...       ...
    7FhZTWILQj -2.906357  1.261039 -0.780273 -0.537237
    4pUDPM4eGq -2.042512 -0.464382 -0.382080  1.132612
    B8dUgUzwTi -1.506637 -0.364435  1.087891  0.297653
    hErlVYjVv9  1.477453 -0.495515 -0.713867  1.438427
    1BKN3o7YLs  0.127535 -0.349812 -0.881836  0.489827
    9S4Ekn7zga  1.445518 -2.095149  0.031982  0.373204
    xN1dNn6OV6  1.425017 -0.983995 -0.363281 -0.224502

    [30 rows x 4 columns]
    """
    df = DataFrame(tm.getSeriesData())
    df.A = df.A.astype('float32')
    df.B = df.B.astype('float32')
    df.C = df.C.astype('float16')
    df.D = df.D.astype('float64')
    return df
Example #4
0
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('int32')
    df.B = np.ones(len(df.B), dtype='uint64')
    df.C = df.C.astype('uint8')
    df.D = df.C.astype('int64')
    return df