本文整理汇总了Python中pandas.core.frame.DataFrame.from_csv方法的典型用法代码示例。如果您正苦于以下问题：Python DataFrame.from_csv方法的具体用法？Python DataFrame.from_csv怎么用？Python DataFrame.from_csv使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pandas.core.frame.DataFrame的用法示例。
在下文中一共展示了DataFrame.from_csv方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: from_csv
# 需要导入模块: from pandas.core.frame import DataFrame [as 别名]
# 或者: from pandas.core.frame.DataFrame import from_csv [as 别名]
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