Python pandas.read_fwf方法代碼示例

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def test_fwf_colspecs_None(self):
        # GH 7079
        data = """\
123456
456789
"""
        colspecs = [(0, 3), (3, None)]
        result = read_fwf(StringIO(data), colspecs=colspecs, header=None)
        expected = DataFrame([[123, 456], [456, 789]])
        tm.assert_frame_equal(result, expected)

        colspecs = [(None, 3), (3, 6)]
        result = read_fwf(StringIO(data), colspecs=colspecs, header=None)
        expected = DataFrame([[123, 456], [456, 789]])
        tm.assert_frame_equal(result, expected)

        colspecs = [(0, None), (3, None)]
        result = read_fwf(StringIO(data), colspecs=colspecs, header=None)
        expected = DataFrame([[123456, 456], [456789, 789]])
        tm.assert_frame_equal(result, expected)

        colspecs = [(None, None), (3, 6)]
        result = read_fwf(StringIO(data), colspecs=colspecs, header=None)
        expected = DataFrame([[123456, 456], [456789, 789]])
        tm.assert_frame_equal(result, expected) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def test_fwf_compression(self):
        try:
            import gzip
            import bz2
        except ImportError:
            pytest.skip("Need gzip and bz2 to run this test")

        data = """1111111111
        2222222222
        3333333333""".strip()
        widths = [5, 5]
        names = ['one', 'two']
        expected = read_fwf(StringIO(data), widths=widths, names=names)
        if compat.PY3:
            data = bytes(data, encoding='utf-8')
        comps = [('gzip', gzip.GzipFile), ('bz2', bz2.BZ2File)]
        for comp_name, compresser in comps:
            with tm.ensure_clean() as path:
                tmp = compresser(path, mode='wb')
                tmp.write(data)
                tmp.close()
                result = read_fwf(path, widths=widths, names=names,
                                  compression=comp_name)
                tm.assert_frame_equal(result, expected) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def load_local_file(self, interval):
        # Read in data
        headings = ['probe', 'year', 'doy', 'hour', 'minute', 'second',
                    'naverage', 'Bx', 'By', 'Bz', '|B|',
                    'sigma_Bx', 'sigma_By', 'sigma_Bz']

        colspecs = [(1, 2), (2, 4), (4, 7), (7, 9), (9, 11), (11, 13),
                    (13, 15), (15, 22), (22, 29), (29, 36), (36, 42), (42, 48),
                    (48, 54), (54, 60)]
        data = pd.read_fwf(self.local_path(interval), names=headings,
                           header=None, colspecs=colspecs)

        # Process data
        data['year'] += 1900
        # Convert date info to datetime
        data['Time'] = pd.to_datetime(data['year'], format='%Y') + \
            pd.to_timedelta(data['doy'] - 1, unit='d') + \
            pd.to_timedelta(data['hour'], unit='h') + \
            pd.to_timedelta(data['minute'], unit='m') + \
            pd.to_timedelta(data['second'], unit='s')
        data = data.drop(['year', 'doy', 'hour', 'minute', 'second'], axis=1)
        data = data.set_index('Time', drop=False)
        return data 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def get_ghcnd_stn_metadata(fname=None, download=False):
    """
    Get the ghcnd station metadata from ghcnd-stations.txt.
    China station start with "CHM000...", like "CHM00054511"
    
    Args:
        fname (string, optional): You can specify the station metadata file. 
                                  Defaults to download the file from website.
    
    Returns:
        [type]: [description]

    Examples:
    >>> stnmd = get_ghcnd_stn_metadata()
    """
    
    if fname == None:
        fname = get_cache_file("pub/data/ghcn/daily/", "ghcnd-stations.txt", name="GHCN")
        if not fname.is_file() or download:
            url = 'https://www1.ncdc.noaa.gov/pub/data/ghcn/daily/ghcnd-stations.txt'
            urllib.request.urlretrieve(url, fname)
    md = pd.read_fwf(fname, colspecs=[(0,12), (12,21), (21,31), (31,38), (38,69)],
                        names=['station','lat','lon','elev','name'])
    return md 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def read_fwf(
        cls, filepath_or_buffer, colspecs="infer", widths=None, infer_nrows=100, **kwds
    ):
        ErrorMessage.default_to_pandas("`read_fwf`")
        pd_obj = pandas.read_fwf(
            filepath_or_buffer,
            colspecs=colspecs,
            widths=widths,
            infer_nrows=infer_nrows,
            **kwds,
        )
        if isinstance(pd_obj, pandas.DataFrame):
            return cls.from_pandas(pd_obj)
        if isinstance(pd_obj, pandas.io.parsers.TextFileReader):
            # Overwriting the read method should return a Modin DataFrame for calls
            # to __next__ and get_chunk
            pd_read = pd_obj.read
            pd_obj.read = lambda *args, **kwargs: cls.from_pandas(
                pd_read(*args, **kwargs)
            )
        return pd_obj 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def test_fwf_file_usecols(usecols):
    fwf_data = """a       b           c          d
id8141  360.242940  149.910199 11950.7
id1594  444.953632  166.985655 11788.4
id1849  364.136849  183.628767 11806.2
id1230  413.836124  184.375703 11916.8
id1948  502.953953  173.237159 12468.3"""

    setup_fwf_file(overwrite=True, fwf_data=fwf_data)

    pandas_df = pandas.read_fwf(TEST_FWF_FILENAME, usecols=usecols)
    modin_df = pd.read_fwf(TEST_FWF_FILENAME, usecols=usecols)

    df_equals(modin_df, pandas_df)

    teardown_fwf_file() 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def test_fwf_file_parse_dates():
    dates = pandas.date_range("2000", freq="h", periods=10)
    fwf_data = "col1 col2        col3 col4"
    for i in range(10, 20):
        fwf_data = fwf_data + "\n{col1}   {col2}  {col3}   {col4}".format(
            col1=str(i),
            col2=str(dates[i - 10].date()),
            col3=str(i),
            col4=str(dates[i - 10].time()),
        )

    setup_fwf_file(overwrite=True, fwf_data=fwf_data)

    pandas_df = pandas.read_fwf(TEST_FWF_FILENAME, parse_dates=[["col2", "col4"]])
    modin_df = pd.read_fwf(TEST_FWF_FILENAME, parse_dates=[["col2", "col4"]])
    df_equals(modin_df, pandas_df)

    pandas_df = pandas.read_fwf(
        TEST_FWF_FILENAME, parse_dates={"time": ["col2", "col4"]}
    )
    modin_df = pd.read_fwf(TEST_FWF_FILENAME, parse_dates={"time": ["col2", "col4"]})
    df_equals(modin_df, pandas_df)

    teardown_fwf_file() 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def ReadFemResp1995():
    """Reads respondent data from NSFG Cycle 5.

    returns: DataFrame
    """
    dat_file = '1995FemRespData.dat.gz'
    names = ['cmintvw', 'timesmar', 'cmmarrhx', 'cmbirth', 'finalwgt']
    colspecs = [(12360-1, 12363),
                (4637-1, 4638),
                (11759-1, 11762),
                (14-1, 16),
                (12350-1, 12359)]
    df = pd.read_fwf(dat_file, 
                         compression='gzip', 
                         colspecs=colspecs, 
                         names=names)

    df.timesmar.replace([98, 99], np.nan, inplace=True)
    df['evrmarry'] = (df.timesmar > 0)

    CleanData(df)
    return df 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def ps(self, args=None, options='', all=True, verbose=True,
           as_frame='auto', raise_on_error=True):
        if args is None:
            args = ''
        if all:
            args += 'A'
        if verbose:
            args += 'f'
        if len(args) > 0 and args[0] != '-':
            args = '-' + args

        results = self.wait(('ps %s %s' % (args, options)).strip(),
                            raise_on_error=raise_on_error)

        if as_frame == 'auto':
            as_frame = has_pandas

        if as_frame:
            if not has_pandas:
                raise ImportError("Unable to import pandas")
            df = pd.read_fwf(StringIO(results))
            cmd_loc = df.columns.get_loc('CMD')
            if cmd_loc < len(df.columns):
                col = cmd_loc.fillna('')
                for i in range(cmd_loc + 1, len(df.columns)):
                    col = col + df.icol(i).fillna('')
                df['CMD'] = col
            return df

        return results 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def test_BytesIO_input(self):
        if not compat.PY3:
            pytest.skip(
                "Bytes-related test - only needs to work on Python 3")

        result = read_fwf(BytesIO("שלום\nשלום".encode('utf8')), widths=[
            2, 2], encoding='utf8')
        expected = DataFrame([["של", "ום"]], columns=["של", "ום"])
        tm.assert_frame_equal(result, expected) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def test_fwf_colspecs_is_list_or_tuple_of_two_element_tuples(self):
        data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""

        with tm.assert_raises_regex(TypeError,
                                    'Each column specification '
                                    'must be.+'):
            read_fwf(StringIO(data), [('a', 1)]) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def test_fwf_regression(self):
        # GH 3594
        # turns out 'T060' is parsable as a datetime slice!

        tzlist = [1, 10, 20, 30, 60, 80, 100]
        ntz = len(tzlist)
        tcolspecs = [16] + [8] * ntz
        tcolnames = ['SST'] + ["T%03d" % z for z in tzlist[1:]]
        data = """  2009164202000   9.5403  9.4105  8.6571  7.8372  6.0612  5.8843  5.5192
  2009164203000   9.5435  9.2010  8.6167  7.8176  6.0804  5.8728  5.4869
  2009164204000   9.5873  9.1326  8.4694  7.5889  6.0422  5.8526  5.4657
  2009164205000   9.5810  9.0896  8.4009  7.4652  6.0322  5.8189  5.4379
  2009164210000   9.6034  9.0897  8.3822  7.4905  6.0908  5.7904  5.4039
"""

        df = read_fwf(StringIO(data),
                      index_col=0,
                      header=None,
                      names=tcolnames,
                      widths=tcolspecs,
                      parse_dates=True,
                      date_parser=lambda s: datetime.strptime(s, '%Y%j%H%M%S'))

        for c in df.columns:
            res = df.loc[:, c]
            assert len(res) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def test_comment_fwf(self):
        data = """
  1   2.   4  #hello world
  5  NaN  10.0
"""
        expected = np.array([[1, 2., 4],
                             [5, np.nan, 10.]])
        df = read_fwf(StringIO(data), colspecs=[(0, 3), (4, 9), (9, 25)],
                      comment='#')
        tm.assert_almost_equal(df.values, expected) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def test_1000_fwf(self):
        data = """
 1 2,334.0    5
10   13     10.
"""
        expected = np.array([[1, 2334., 5],
                             [10, 13, 10]])
        df = read_fwf(StringIO(data), colspecs=[(0, 3), (3, 11), (12, 16)],
                      thousands=',')
        tm.assert_almost_equal(df.values, expected) 

# 需要導入模塊: import pandas [as 別名]
# 或者: from pandas import read_fwf [as 別名]
def test_bool_header_arg(self):
        # see gh-6114
        data = """\
MyColumn
   a
   b
   a
   b"""
        for arg in [True, False]:
            with pytest.raises(TypeError):
                read_fwf(StringIO(data), header=arg)