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iris.pandas.as_data_frame() doctests full width #5057

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Merged
stephenworsley merged 3 commits into from
Nov 10, 2022
Merged

iris.pandas.as_data_frame() doctests full width #5057

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219d547
iris.pandas.as_data_frame doctests full width.
trexfeathers Nov 10, 2022
31f5ea6
NetCDF4 pin to enable RTD build.
trexfeathers Nov 10, 2022
9b66cdd
Revert "NetCDF4 pin to enable RTD build."
trexfeathers Nov 10, 2022
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79 changes: 41 additions & 38 deletions lib/iris/pandas.py
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Original file line number Diff line number Diff line change
Expand Up @@ -678,6 +678,9 @@ def as_data_frame(
--------
>>> import iris
>>> from iris.pandas import as_data_frame
>>> import pandas as pd
>>> pd.set_option('display.width', 1000)
>>> pd.set_option('display.max_columns', 1000)

Convert a simple :class:`~iris.cube.Cube`:

Expand Down Expand Up @@ -708,19 +711,19 @@ def as_data_frame(
>>> df = as_data_frame(cube, add_aux_coords=True)
>>> print(df)
... # doctest: +NORMALIZE_WHITESPACE
surface_temperature ... forecast_reference_time
time latitude longitude ...
2006-04-16 00:00:00 -4.999992 0.000000 301.659271 ... 2006-04-16 12:00:00
0.833333 301.785004 ... 2006-04-16 12:00:00
1.666667 301.820984 ... 2006-04-16 12:00:00
2.500000 301.865234 ... 2006-04-16 12:00:00
3.333333 301.926819 ... 2006-04-16 12:00:00
... ... ... ...
2010-09-16 00:00:00 4.444450 355.833313 298.779938 ... 2010-09-16 12:00:00
356.666656 298.913147 ... 2010-09-16 12:00:00
357.500000 NaN ... 2010-09-16 12:00:00
358.333313 NaN ... 2010-09-16 12:00:00
359.166656 298.995148 ... 2010-09-16 12:00:00
surface_temperature forecast_period forecast_reference_time
time latitude longitude
2006-04-16 00:00:00 -4.999992 0.000000 301.659271 0 2006-04-16 12:00:00
0.833333 301.785004 0 2006-04-16 12:00:00
1.666667 301.820984 0 2006-04-16 12:00:00
2.500000 301.865234 0 2006-04-16 12:00:00
3.333333 301.926819 0 2006-04-16 12:00:00
... ... ... ...
2010-09-16 00:00:00 4.444450 355.833313 298.779938 0 2010-09-16 12:00:00
356.666656 298.913147 0 2010-09-16 12:00:00
357.500000 NaN 0 2010-09-16 12:00:00
358.333313 NaN 0 2010-09-16 12:00:00
359.166656 298.995148 0 2010-09-16 12:00:00
<BLANKLINE>
[419904 rows x 3 columns]

Expand All @@ -730,19 +733,19 @@ def as_data_frame(
>>> df['STASH'] = str(cube.attributes['STASH'])
>>> print(df)
... # doctest: +NORMALIZE_WHITESPACE
surface_temperature ... STASH
time latitude longitude ...
2006-04-16 00:00:00 -4.999992 0.000000 301.659271 ... m01s00i024
0.833333 301.785004 ... m01s00i024
1.666667 301.820984 ... m01s00i024
2.500000 301.865234 ... m01s00i024
3.333333 301.926819 ... m01s00i024
... ... ... ...
2010-09-16 00:00:00 4.444450 355.833313 298.779938 ... m01s00i024
356.666656 298.913147 ... m01s00i024
357.500000 NaN ... m01s00i024
358.333313 NaN ... m01s00i024
359.166656 298.995148 ... m01s00i024
surface_temperature forecast_period forecast_reference_time STASH
time latitude longitude
2006-04-16 00:00:00 -4.999992 0.000000 301.659271 0 2006-04-16 12:00:00 m01s00i024
0.833333 301.785004 0 2006-04-16 12:00:00 m01s00i024
1.666667 301.820984 0 2006-04-16 12:00:00 m01s00i024
2.500000 301.865234 0 2006-04-16 12:00:00 m01s00i024
3.333333 301.926819 0 2006-04-16 12:00:00 m01s00i024
... ... ... ... ...
2010-09-16 00:00:00 4.444450 355.833313 298.779938 0 2010-09-16 12:00:00 m01s00i024
356.666656 298.913147 0 2010-09-16 12:00:00 m01s00i024
357.500000 NaN 0 2010-09-16 12:00:00 m01s00i024
358.333313 NaN 0 2010-09-16 12:00:00 m01s00i024
359.166656 298.995148 0 2010-09-16 12:00:00 m01s00i024
<BLANKLINE>
[419904 rows x 4 columns]

Expand All @@ -753,18 +756,18 @@ def as_data_frame(
>>> df.reset_index(inplace=True)
>>> print(df)
... # doctest: +NORMALIZE_WHITESPACE
time latitude ... forecast_reference_time STASH
0 2006-04-16 00:00:00 -4.999992 ... 2006-04-16 12:00:00 m01s00i024
1 2006-04-16 00:00:00 -4.999992 ... 2006-04-16 12:00:00 m01s00i024
2 2006-04-16 00:00:00 -4.999992 ... 2006-04-16 12:00:00 m01s00i024
3 2006-04-16 00:00:00 -4.999992 ... 2006-04-16 12:00:00 m01s00i024
4 2006-04-16 00:00:00 -4.999992 ... 2006-04-16 12:00:00 m01s00i024
... ... ... ... ... ...
419899 2010-09-16 00:00:00 4.444450 ... 2010-09-16 12:00:00 m01s00i024
419900 2010-09-16 00:00:00 4.444450 ... 2010-09-16 12:00:00 m01s00i024
419901 2010-09-16 00:00:00 4.444450 ... 2010-09-16 12:00:00 m01s00i024
419902 2010-09-16 00:00:00 4.444450 ... 2010-09-16 12:00:00 m01s00i024
419903 2010-09-16 00:00:00 4.444450 ... 2010-09-16 12:00:00 m01s00i024
time latitude longitude surface_temperature forecast_period forecast_reference_time STASH
0 2006-04-16 00:00:00 -4.999992 0.000000 301.659271 0 2006-04-16 12:00:00 m01s00i024
1 2006-04-16 00:00:00 -4.999992 0.833333 301.785004 0 2006-04-16 12:00:00 m01s00i024
2 2006-04-16 00:00:00 -4.999992 1.666667 301.820984 0 2006-04-16 12:00:00 m01s00i024
3 2006-04-16 00:00:00 -4.999992 2.500000 301.865234 0 2006-04-16 12:00:00 m01s00i024
4 2006-04-16 00:00:00 -4.999992 3.333333 301.926819 0 2006-04-16 12:00:00 m01s00i024
... ... ... ... ... ... ...
419899 2010-09-16 00:00:00 4.444450 355.833313 298.779938 0 2010-09-16 12:00:00 m01s00i024
419900 2010-09-16 00:00:00 4.444450 356.666656 298.913147 0 2010-09-16 12:00:00 m01s00i024
419901 2010-09-16 00:00:00 4.444450 357.500000 NaN 0 2010-09-16 12:00:00 m01s00i024
419902 2010-09-16 00:00:00 4.444450 358.333313 NaN 0 2010-09-16 12:00:00 m01s00i024
419903 2010-09-16 00:00:00 4.444450 359.166656 298.995148 0 2010-09-16 12:00:00 m01s00i024
<BLANKLINE>
[419904 rows x 7 columns]

Expand Down