scipp.io.csv.load_csv#

scipp.io.csv.load_csv(filename, *, sep=',', data_columns=None, header_parser=None)#

Load a CSV file as a dataset.

This function currently uses Pandas to load the file and converts the result into a scipp.Dataset. Pandas is not a hard dependency of Scipp and will thus not be installed automatically, so you need to install it manually.

load_csv exists to conveniently load simple CSV files. If a file cannot be loaded directly, consider using Pandas directly. For example, use pandas.read_csv() to load the file into a data frame and scipp.compat.pandas_compat.from_pandas() to convert the data frame into a dataset.

Parameters
Returns

Dataset – The loaded data as a dataset.

Examples

Given the following CSV ‘file’:

>>> from io import StringIO
>>> csv_content = '''a [m],b [s],c
... 1,5,9
... 2,6,10
... 3,7,11
... 4,8,12'''

By default, it will be loaded as

>>> sc.io.load_csv(StringIO(csv_content))
<scipp.Dataset>
Dimensions: Sizes[row:4, ]
Data:
  a [m]                       int64  [dimensionless]  (row)  [1, 2, 3, 4]
  b [s]                       int64  [dimensionless]  (row)  [5, 6, 7, 8]
  c                           int64  [dimensionless]  (row)  [9, 10, 11, 12]

In this example, the column headers encode units. They can be parsed into actual units:

>>> sc.io.load_csv(StringIO(csv_content), header_parser='bracket')
<scipp.Dataset>
Dimensions: Sizes[row:4, ]
Data:
  a                           int64              [m]  (row)  [1, 2, 3, 4]
  b                           int64              [s]  (row)  [5, 6, 7, 8]
  c                           int64        <no unit>  (row)  [9, 10, 11, 12]

It is possible to select which columns are stored as data:

>>> sc.io.load_csv(
...     StringIO(csv_content),
...     header_parser='bracket',
...     data_columns='a',
... )
<scipp.Dataset>
Dimensions: Sizes[row:4, ]
Coordinates:
* b                           int64              [s]  (row)  [5, 6, 7, 8]
* c                           int64        <no unit>  (row)  [9, 10, 11, 12]
Data:
  a                           int64              [m]  (row)  [1, 2, 3, 4]