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| author | Pranab Das <31024886+pranabdas@users.noreply.github.com> | 2022-07-02 12:04:14 +0800 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2022-07-02 00:04:14 -0400 |
| commit | 3d9cacc100e1b9382a543f000d0df44180cff122 (patch) | |
| tree | 0af40c6b43d8bf6f2f5baa0a5196f3afd5cc998a /numpy/lib/npyio.py | |
| parent | 860a12ede7a4521debc16ef8c3a8b3d182b65c7a (diff) | |
| download | numpy-3d9cacc100e1b9382a543f000d0df44180cff122.tar.gz | |
DOC: Clarify loadtxt input cols requirement (#21861)
Also add an example to illustrate how usecols can be used
to read a file with varying number of fields.
Diffstat (limited to 'numpy/lib/npyio.py')
| -rw-r--r-- | numpy/lib/npyio.py | 16 |
1 files changed, 14 insertions, 2 deletions
diff --git a/numpy/lib/npyio.py b/numpy/lib/npyio.py index 52bcf25f8..471f85976 100644 --- a/numpy/lib/npyio.py +++ b/numpy/lib/npyio.py @@ -1067,8 +1067,6 @@ def loadtxt(fname, dtype=float, comments='#', delimiter=None, r""" Load data from a text file. - Each row in the text file must have the same number of values. - Parameters ---------- fname : file, str, pathlib.Path, list of str, generator @@ -1171,6 +1169,11 @@ def loadtxt(fname, dtype=float, comments='#', delimiter=None, `genfromtxt` function provides more sophisticated handling of, e.g., lines with missing values. + Each row in the input text file must have the same number of values to be + able to read all values. If all rows do not have same number of values, a + subset of up to n columns (where n is the least number of values present + in all rows) can be read by specifying the columns via `usecols`. + .. versionadded:: 1.10.0 The strings produced by the Python float.hex method can be used as @@ -1279,6 +1282,15 @@ def loadtxt(fname, dtype=float, comments='#', delimiter=None, >>> np.loadtxt(s, dtype="U", delimiter=",", quotechar='"') array('Hello, my name is "Monty"!', dtype='<U26') + Read subset of columns when all rows do not contain equal number of values: + + >>> d = StringIO("1 2\n2 4\n3 9 12\n4 16 20") + >>> np.loadtxt(d, usecols=(0, 1)) + array([[ 1., 2.], + [ 2., 4.], + [ 3., 9.], + [ 4., 16.]]) + """ if like is not None: |