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GMT_DATASET.to_dataframe: Return an empty DataFrame if a file contains no data #3131
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| Original file line number | Diff line number | Diff line change |
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| """ | ||
| Tests for GMT_DATASET data type. | ||
| """ | ||
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| from pathlib import Path | ||
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| import pandas as pd | ||
| import pytest | ||
| from pygmt.clib import Session | ||
| from pygmt.helpers import GMTTempFile | ||
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| def dataframe_from_pandas(filepath_or_buffer, sep=r"\s+", comment="#", header=None): | ||
| """ | ||
| Read tabular data as pandas.DataFrame object using pandas.read_csv(). | ||
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| The parameters have the same meaning as in ``pandas.read_csv()``. | ||
| """ | ||
| try: | ||
| df = pd.read_csv(filepath_or_buffer, sep=sep, comment=comment, header=header) | ||
| except pd.errors.EmptyDataError: | ||
| # Return an empty DataFrame if the file contains no data | ||
| return pd.DataFrame() | ||
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| # By default, pandas reads text strings with whitespaces as multiple columns, but | ||
| # GMT concatenates all trailing text as a single string column. Need do find all | ||
| # string columns (with dtype="object") and combine them into a single string column. | ||
| string_columns = df.select_dtypes(include=["object"]).columns | ||
| if len(string_columns) > 1: | ||
| df[string_columns[0]] = df[string_columns].apply(lambda x: " ".join(x), axis=1) | ||
| df = df.drop(string_columns[1:], axis=1) | ||
| # Convert 'object' to 'string' type | ||
| df = df.convert_dtypes( | ||
| convert_string=True, | ||
| convert_integer=False, | ||
| convert_boolean=False, | ||
| convert_floating=False, | ||
| ) | ||
| return df | ||
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| def dataframe_from_gmt(fname): | ||
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Member
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. For reference, GMT provides two special/undocumented modules |
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| """ | ||
| Read tabular data as pandas.DataFrame using GMT virtual file. | ||
| """ | ||
| with Session() as lib: | ||
| with lib.virtualfile_out(kind="dataset") as vouttbl: | ||
| lib.call_module("read", f"{fname} {vouttbl} -Td") | ||
| df = lib.virtualfile_to_dataset(vfname=vouttbl) | ||
| return df | ||
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| @pytest.mark.benchmark | ||
| def test_dataset(): | ||
| """ | ||
| Test the basic functionality of GMT_DATASET. | ||
| """ | ||
| with GMTTempFile(suffix=".txt") as tmpfile: | ||
| with Path(tmpfile.name).open(mode="w") as fp: | ||
| print(">", file=fp) | ||
| print("1.0 2.0 3.0 TEXT1 TEXT23", file=fp) | ||
| print("4.0 5.0 6.0 TEXT4 TEXT567", file=fp) | ||
| print(">", file=fp) | ||
| print("7.0 8.0 9.0 TEXT8 TEXT90", file=fp) | ||
| print("10.0 11.0 12.0 TEXT123 TEXT456789", file=fp) | ||
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| df = dataframe_from_gmt(tmpfile.name) | ||
| expected_df = dataframe_from_pandas(tmpfile.name, comment=">") | ||
| pd.testing.assert_frame_equal(df, expected_df) | ||
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| def test_dataset_empty(): | ||
| """ | ||
| Make sure that an empty DataFrame is returned if a file contains no data. | ||
| """ | ||
| with GMTTempFile(suffix=".txt") as tmpfile: | ||
| with Path(tmpfile.name).open(mode="w") as fp: | ||
| print("# This is a comment line.", file=fp) | ||
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| df = dataframe_from_gmt(tmpfile.name) | ||
| assert df.empty # Empty DataFrame | ||
| expected_df = dataframe_from_pandas(tmpfile.name) | ||
| pd.testing.assert_frame_equal(df, expected_df) | ||
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An empty
pd.DataFrame()won't have any columns. Should there still be columns returned (even if there are no rows)? How would this work with #3117 for example?Uh oh!
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A DataFrame with columns but no rows is still empty. So I guess it's fine.
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Column names are set here like so:
pygmt/pygmt/clib/session.py
Lines 1853 to 1861 in 1eb6dec
So we would do something like:
But setting column names to
["col1", "col2"]errors with:--------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In[8], line 1 ----> 1 df.columns = ["col1", "col2"] File ~/mambaforge/envs/pygmt/lib/python3.12/site-packages/pandas/core/generic.py:6310, in NDFrame.__setattr__(self, name, value) 6308 try: 6309 object.__getattribute__(self, name) -> 6310 return object.__setattr__(self, name, value) 6311 except AttributeError: 6312 pass File properties.pyx:69, in pandas._libs.properties.AxisProperty.__set__() File ~/mambaforge/envs/pygmt/lib/python3.12/site-packages/pandas/core/generic.py:813, in NDFrame._set_axis(self, axis, labels) 808 """ 809 This is called from the cython code when we set the `index` attribute 810 directly, e.g. `series.index = [1, 2, 3]`. 811 """ 812 labels = ensure_index(labels) --> 813 self._mgr.set_axis(axis, labels) 814 self._clear_item_cache() File ~/mambaforge/envs/pygmt/lib/python3.12/site-packages/pandas/core/internals/managers.py:238, in BaseBlockManager.set_axis(self, axis, new_labels) 236 def set_axis(self, axis: AxisInt, new_labels: Index) -> None: 237 # Caller is responsible for ensuring we have an Index object. --> 238 self._validate_set_axis(axis, new_labels) 239 self.axes[axis] = new_labels File ~/mambaforge/envs/pygmt/lib/python3.12/site-packages/pandas/core/internals/base.py:98, in DataManager._validate_set_axis(self, axis, new_labels) 95 pass 97 elif new_len != old_len: ---> 98 raise ValueError( 99 f"Length mismatch: Expected axis has {old_len} elements, new " 100 f"values have {new_len} elements" 101 ) ValueError: Length mismatch: Expected axis has 0 elements, new values have 2 elementsThere was a problem hiding this comment.
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I think we need to refactor
GMT_DATASET.to_dataframe()to accept more panda-specific parameters (e.g.,column_names,index_col). The thevirtualfile_to_datasetwill be called like:There was a problem hiding this comment.
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Right, so moving these lines that handle the column names from
virtualfile_to_datasettoto_dataframe:pygmt/pygmt/clib/session.py
Lines 1861 to 1863 in 62eb5d6
Do you want to just do that in #3117? Or have a separate PR to handle this?
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Better to do it in a separate PR so that #3117 can focus on parsing the column names from header.
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Done in #3140, so need to refactor this PR after #3140 is merged.