windng
Check-in [b0ca1456a2]
Not logged in

Many hyperlinks are disabled.
Use anonymous login to enable hyperlinks.

Overview
Comment:Drop support for pandas <= 0.15.1 in windng.io.
Downloads: Tarball | ZIP archive | SQL archive
Timelines: family | ancestors | descendants | both | trunk
Files: files | file ages | folders
SHA1:b0ca1456a2e9d840e90fbb8502eedb79757bfa2a
User & Date: goyo 2015-10-20 06:57:37
Context
2015-10-28
23:48
Improvements to turbulence(). check-in: b9977fb29f user: goyo tags: trunk
2015-10-20
06:57
Drop support for pandas <= 0.15.1 in windng.io. check-in: b0ca1456a2 user: goyo tags: trunk
2015-10-19
13:30
pandas.TimeSeries is deprecated. Fixes [3d4d407b06]. check-in: 5be8ea71ab user: goyo tags: trunk
Changes
Hide Diffs Unified Diffs Ignore Whitespace Patch

Changes to windng/io.py.

190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
    return d.get(s, default)

def read_vortex(filepath_or_buffer, **kwargs):
    """Read Vortex file into DataFrame."""
    f = get_filepath_or_buffer(filepath_or_buffer)[0]
    meta = read_vortex_metadata(f)
    kwargs.setdefault('header', 0)
    if pd.__version__ <= '0.15.1':
        kwargs.setdefault('skiprows', 2)
    else:
        # Pandas > 0.15.1 skips blank lines automatically.
        kwargs.setdefault('skiprows', 1)
    kwargs.setdefault('freq', 'H')

    df = read_wind(f, **kwargs)
    df.index.name = 'YYYYMMDD_HHMM'
    columns = pd.MultiIndex.from_tuples(
        [_parse_vortex_field_header(s, meta['Height']) for s in df.columns],
        names=['kind', 'name', 'height', 'signal']







<
<
<
<
|







190
191
192
193
194
195
196




197
198
199
200
201
202
203
204
    return d.get(s, default)

def read_vortex(filepath_or_buffer, **kwargs):
    """Read Vortex file into DataFrame."""
    f = get_filepath_or_buffer(filepath_or_buffer)[0]
    meta = read_vortex_metadata(f)
    kwargs.setdefault('header', 0)




    kwargs.setdefault('skiprows', 1)
    kwargs.setdefault('freq', 'H')

    df = read_wind(f, **kwargs)
    df.index.name = 'YYYYMMDD_HHMM'
    columns = pd.MultiIndex.from_tuples(
        [_parse_vortex_field_header(s, meta['Height']) for s in df.columns],
        names=['kind', 'name', 'height', 'signal']