Python pandas.core.frame.DataFrame.from_csv() Examples
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code examples of pandas.core.frame.DataFrame.from_csv().
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Example #1
| Source File: series.py From Computable with MIT License | 5 votes |
|
def from_csv(cls, path, sep=',', parse_dates=True, header=None,
index_col=0, encoding=None, infer_datetime_format=False):
"""
Read delimited file into Series
Parameters
----------
path : string file path or file handle / StringIO
sep : string, default ','
Field delimiter
parse_dates : boolean, default True
Parse dates. Different default from read_table
header : int, default 0
Row to use at header (skip prior rows)
index_col : int or sequence, default 0
Column to use for index. If a sequence is given, a MultiIndex
is used. Different default from read_table
encoding : string, optional
a string representing the encoding to use if the contents are
non-ascii, for python versions prior to 3
infer_datetime_format: boolean, default False
If True and `parse_dates` is True for a column, try to infer the
datetime format based on the first datetime string. If the format
can be inferred, there often will be a large parsing speed-up.
Returns
-------
y : Series
"""
from pandas.core.frame import DataFrame
df = DataFrame.from_csv(path, header=header, index_col=index_col,
sep=sep, parse_dates=parse_dates,
encoding=encoding,
infer_datetime_format=infer_datetime_format)
result = df.icol(0)
result.index.name = result.name = None
return result
