read_table

read_table(
    path: Path ,
    what: str = nothing,
    skip: int = 0,
)-> ‘pd.DataFrame’

Read one strict CSV table.

Every cell arrives as text and the caller coerces it, so a column’s meaning is the field’s rather than whatever pandas inferred from the rows it happened to see. Only a truly empty cell is null: an empty cell means unset, and a document which writes NA means the string.

Parameters

Parameter	Description
path	The CSV file to read.
what	What a table with no columns fails to state, for that error message.
skip	Lines above the header, for a format which states something of its own before its table. Read past before the table is parsed at all, so nothing downstream has to agree about what those lines were. Row numbers in errors still count from the top of the file, so they name the line a reader would look at.

Examples

import tempfile
from pathlib import Path
from dascore.utils.tables import read_table
with tempfile.TemporaryDirectory() as folder:
    path = Path(folder) / "coupling.csv"
    _ = path.write_text("group,value\nrail,true\n")
    frame = read_table(path)
list(frame.columns), frame["value"][0]

(['group', 'value'], 'true')