importpandas as pdprint(“**取消第一行作为表头*****”)
data2= pd.read_csv(‘rating.csv’,header=None)print(“**为各个字段取名**“)
data3= pd.read_csv(‘rating.csv’,names=[‘user_id’,’book_id’,’rating’])print(“**将某一字段设为索引**“)
data3= pd.read_csv(‘rating.csv’,
names=[‘user_id’,’book_id’,’rating’],
index_col= “user_id”)print(“**用sep参数设置分隔符**“)
data4= pd.read_csv(‘rating.csv’,
names=[‘user_id’,’book_id’,’rating’],
sep=’,’)print(“**自动补全缺失数据为NaN**“)
data5= pd.read_csv(‘data.csv’,header=None)
read_csv(filepath_or_buffer: Union[ForwardRef(‘PathLike[str]’), str, IO[~T], io.RawIOBase, io.BufferedIOBase, io.TextIOBase, _io.TextIOWrapper, mmap.mmap], sep=, delimiter=None, header=’infer’, names=None, index_col=None, usecols=None, squeeze=False, prefix=None, mangle_dupe_cols=True, dtype=None, engine=None, converters=None, true_values=None, false_values=None, skipinitialspace=False, skiprows=None, skipfooter=0, nrows=None, na_values=None, keep_default_na=True, na_filter=True, verbose=False, skip_blank_lines=True, parse_dates=False, infer_datetime_format=False, keep_date_col=False, date_parser=None, dayfirst=False, cache_dates=True, iterator=False, chunksize=None, compression=’infer’, thousands=None, decimal: str = ‘.’, lineterminator=None, quotechar='”‘, quoting=0, doublequote=True, escapechar=None, comment=None, encoding=None, dialect=None, error_bad_lines=True, warn_bad_lines=True, delim_whitespace=False, low_memory=True, memory_map=False, float_precision=None, storage_options: Union[Dict[str, Any], NoneType] = None)
Read a comma-separated values (csv) file into DataFrame.
Also supports optionally iterating or breaking of the file
into chunks.
Additional help can be found in the online docs for
IO Tools_.
Parameters
Original: https://blog.csdn.net/weixin_35203943/article/details/114410052
Author: 执壹
Title: python中pd读取csv二进制_python用pd.read_csv()方法来读取csv文件
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