def from_ascii(path, seperator=None, names=True, skip_lines=0, skip_after=0, **kwargs):
"""
Create an in memory DataFrame from an ascii file (whitespace seperated by default).
>>> ds = vx.from_ascii("table.asc")
>>> ds = vx.from_ascii("table.csv", seperator=",", names=["x", "y", "z"])
:param path: file path
:param seperator: value seperator, by default whitespace, use "," for comma seperated values.
:param names: If True, the first line is used for the column names, otherwise provide a list of strings with names
:param skip_lines: skip lines at the start of the file
:param skip_after: skip lines at the end of the file
:param kwargs:
:rtype: DataFrame
"""
import vaex.ext.readcol as rc
ds = vaex.dataframe.DataFrameArrays(path)
if names not in [True, False]:
namelist = names
names = False
else:
namelist = None
data = rc.readcol(path, fsep=seperator, asdict=namelist is None, names=names, skipline=skip_lines, skipafter=skip_after, **kwargs)
if namelist:
for name, array in zip(namelist, data.T):
ds.add_column(name, array)
else:
for name, array in data.items():
ds.add_column(name, array)
return ds
def from_ascii(path, seperator=None, names=True, skip_lines=0, skip_after=0, **kwargs):
"""
Create an in memory DataFrame from an ascii file (whitespace seperated by default).
>>> ds = vx.from_ascii("table.asc")
>>> ds = vx.from_ascii("table.csv", seperator=",", names=["x", "y", "z"])
:param path: file path
:param seperator: value seperator, by default whitespace, use "," for comma seperated values.
:param names: If True, the first line is used for the column names, otherwise provide a list of strings with names
:param skip_lines: skip lines at the start of the file
:param skip_after: skip lines at the end of the file
:param kwargs:
:rtype: DataFrame
"""
import vaex.ext.readcol as rc
ds = vaex.dataframe.DataFrameArrays(path)
if names not in [True, False]:
namelist = names
names = False
else:
namelist = None
data = rc.readcol(path, fsep=seperator, asdict=namelist is None, names=names, skipline=skip_lines, skipafter=skip_after, **kwargs)
if namelist:
for name, array in zip(namelist, data.T):
ds.add_column(name, array)
else:
for name, array in data.items():
ds.add_column(name, array)
return ds
